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SQL As Understood By SQLite sqlite.org

The SQLite library understands most of the standard SQL language. But it does omit some features while at the same time adding a few features of its own. This document attempts to describe precisely what parts of the SQL language SQLite does and does not support. A list of keywords is also provided.

In all of the syntax diagrams that follow, literal text is shown in bold blue. Non-terminal symbols are shown in italic red. Operators that are part of the syntactic markup itself are shown in black roman.

This document is just an overview of the SQL syntax implemented by SQLite. Many low-level productions are omitted. For detailed information on the language that SQLite understands, refer to the source code and the grammar file "parse.y".

SQLite implements the follow syntax:

Details on the implementation of each command are provided in the sequel.


ALTER TABLE

sql-statement ::= ALTER TABLE [database-name .] table-name alteration
alteration ::= RENAME TO new-table-name
alteration ::= ADD [COLUMN] column-def

SQLite's version of the ALTER TABLE command allows the user to rename or add a new column to an existing table. It is not possible to remove a column from a table.

The RENAME TO syntax is used to rename the table identified by [database-name.]table-name to new-table-name. This command cannot be used to move a table between attached databases, only to rename a table within the same database.

If the table being renamed has triggers or indices, then these remain attached to the table after it has been renamed. However, if there are any view definitions, or statements executed by triggers that refer to the table being renamed, these are not automatically modified to use the new table name. If this is required, the triggers or view definitions must be dropped and recreated to use the new table name by hand.

The ADD [COLUMN] syntax is used to add a new column to an existing table. The new column is always appended to the end of the list of existing columns. Column-def may take any of the forms permissable in a CREATE TABLE statement, with the following restrictions:

  • The column may not have a PRIMARY KEY or UNIQUE constraint.
  • The column may not have a default value of CURRENT_TIME, CURRENT_DATE or CURRENT_TIMESTAMP.
  • If a NOT NULL constraint is specified, then the column must have a default value other than NULL.

The execution time of the ALTER TABLE command is independent of the amount of data in the table. The ALTER TABLE command runs as quickly on a table with 10 million rows as it does on a table with 1 row.

After ADD COLUMN has been run on a database, that database will not be readable by SQLite version 3.1.3 and earlier until the database is VACUUMed.


ANALYZE

sql-statement ::= ANALYZE
sql-statement ::= ANALYZE database-name
sql-statement ::= ANALYZE [database-name .] table-name

The ANALYZE command gathers statistics about indices and stores them in a special tables in the database where the query optimizer can use them to help make better index choices. If no arguments are given, all indices in all attached databases are analyzed. If a database name is given as the argument, all indices in that one database are analyzed. If the argument is a table name, then only indices associated with that one table are analyzed.

The initial implementation stores all statistics in a single table named sqlite_stat1. Future enhancements may create additional tables with the same name pattern except with the "1" changed to a different digit. The sqlite_stat1 table cannot be DROPped, but it all the content can be DELETEd which has the same effect.


ATTACH DATABASE

sql-statement ::= ATTACH [DATABASE] database-filename AS database-name

The ATTACH DATABASE statement adds a preexisting database file to the current database connection. If the filename contains punctuation characters it must be quoted. The names 'main' and 'temp' refer to the main database and the database used for temporary tables. These cannot be detached. Attached databases are removed using the DETACH DATABASE statement.

You can read from and write to an attached database and you can modify the schema of the attached database. This is a new feature of SQLite version 3.0. In SQLite 2.8, schema changes to attached databases were not allowed.

You cannot create a new table with the same name as a table in an attached database, but you can attach a database which contains tables whose names are duplicates of tables in the main database. It is also permissible to attach the same database file multiple times.

Tables in an attached database can be referred to using the syntax database-name.table-name. If an attached table doesn't have a duplicate table name in the main database, it doesn't require a database name prefix. When a database is attached, all of its tables which don't have duplicate names become the 'default' table of that name. Any tables of that name attached afterwards require the table prefix. If the 'default' table of a given name is detached, then the last table of that name attached becomes the new default.

Transactions involving multiple attached databases are atomic, assuming that the main database is not ":memory:". If the main database is ":memory:" then transactions continue to be atomic within each individual database file. But if the host computer crashes in the middle of a COMMIT where two or more database files are updated, some of those files might get the changes where others might not. Atomic commit of attached databases is a new feature of SQLite version 3.0. In SQLite version 2.8, all commits to attached databases behaved as if the main database were ":memory:".

There is a compile-time limit of 10 attached database files.


BEGIN TRANSACTION

sql-statement ::= BEGIN [ DEFERRED | IMMEDIATE | EXCLUSIVE ] [TRANSACTION [name]]
sql-statement ::= END [TRANSACTION [name]]
sql-statement ::= COMMIT [TRANSACTION [name]]
sql-statement ::= ROLLBACK [TRANSACTION [name]]

Beginning in version 2.0, SQLite supports transactions with rollback and atomic commit.

The optional transaction name is ignored. SQLite currently does not allow nested transactions.

No changes can be made to the database except within a transaction. Any command that changes the database (basically, any SQL command other than SELECT) will automatically start a transaction if one is not already in effect. Automatically started transactions are committed at the conclusion of the command.

Transactions can be started manually using the BEGIN command. Such transactions usually persist until the next COMMIT or ROLLBACK command. But a transaction will also ROLLBACK if the database is closed or if an error occurs and the ROLLBACK conflict resolution algorithm is specified. See the documentation on the ON CONFLICT clause for additional information about the ROLLBACK conflict resolution algorithm.

In SQLite version 3.0.8 and later, transactions can be deferred, immediate, or exclusive. Deferred means that no locks are acquired on the database until the database is first accessed. Thus with a deferred transaction, the BEGIN statement itself does nothing. Locks are not acquired until the first read or write operation. The first read operation against a database creates a SHARED lock and the first write operation creates a RESERVED lock. Because the acquisition of locks is deferred until they are needed, it is possible that another thread or process could create a separate transaction and write to the database after the BEGIN on the current thread has executed. If the transaction is immediate, then RESERVED locks are acquired on all databases as soon as the BEGIN command is executed, without waiting for the database to be used. After a BEGIN IMMEDIATE, you are guaranteed that no other thread or process will be able to write to the database or do a BEGIN IMMEDIATE or BEGIN EXCLUSIVE. Other processes can continue to read from the database, however. An exclusive transaction causes EXCLUSIVE locks to be acquired on all databases. After a BEGIN EXCLUSIVE, you are guaranteed that no other thread or process will be able to read or write the database until the transaction is complete.

A description of the meaning of SHARED, RESERVED, and EXCLUSIVE locks is available separately.

The default behavior for SQLite version 3.0.8 is a deferred transaction. For SQLite version 3.0.0 through 3.0.7, deferred is the only kind of transaction available. For SQLite version 2.8 and earlier, all transactions are exclusive.

The COMMIT command does not actually perform a commit until all pending SQL commands finish. Thus if two or more SELECT statements are in the middle of processing and a COMMIT is executed, the commit will not actually occur until all SELECT statements finish.

An attempt to execute COMMIT might result in an SQLITE_BUSY return code. This indicates that another thread or process had a read lock on the database that prevented the database from being updated. When COMMIT fails in this way, the transaction remains active and the COMMIT can be retried later after the reader has had a chance to clear.


comment

comment ::= SQL-comment | C-comment
SQL-comment ::= -- single-line
C-comment ::= /* multiple-lines [*/]

Comments aren't SQL commands, but can occur in SQL queries. They are treated as whitespace by the parser. They can begin anywhere whitespace can be found, including inside expressions that span multiple lines.

SQL comments only extend to the end of the current line.

C comments can span any number of lines. If there is no terminating delimiter, they extend to the end of the input. This is not treated as an error. A new SQL statement can begin on a line after a multiline comment ends. C comments can be embedded anywhere whitespace can occur, including inside expressions, and in the middle of other SQL statements. C comments do not nest. SQL comments inside a C comment will be ignored.


COPY

sql-statement ::= COPY [ OR conflict-algorithm ] [database-name .] table-name FROM filename
[ USING DELIMITERS delim ]

The COPY command is available in SQLite version 2.8 and earlier. The COPY command has been removed from SQLite version 3.0 due to complications in trying to support it in a mixed UTF-8/16 environment. In version 3.0, the command-line shell contains a new command .import that can be used as a substitute for COPY.

The COPY command is an extension used to load large amounts of data into a table. It is modeled after a similar command found in PostgreSQL. In fact, the SQLite COPY command is specifically designed to be able to read the output of the PostgreSQL dump utility pg_dump so that data can be easily transferred from PostgreSQL into SQLite.

The table-name is the name of an existing table which is to be filled with data. The filename is a string or identifier that names a file from which data will be read. The filename can be the STDIN to read data from standard input.

Each line of the input file is converted into a single record in the table. Columns are separated by tabs. If a tab occurs as data within a column, then that tab is preceded by a baskslash "\" character. A baskslash in the data appears as two backslashes in a row. The optional USING DELIMITERS clause can specify a delimiter other than tab.

If a column consists of the character "\N", that column is filled with the value NULL.

The optional conflict-clause allows the specification of an alternative constraint conflict resolution algorithm to use for this one command. See the section titled ON CONFLICT for additional information.

When the input data source is STDIN, the input can be terminated by a line that contains only a baskslash and a dot: "\.".


CREATE INDEX

sql-statement ::= CREATE [UNIQUE] INDEX [IF NOT EXISTS] [database-name .] index-name
ON
table-name ( column-name [, column-name]* )
column-name ::= name [ COLLATE collation-name] [ ASC | DESC ]

The CREATE INDEX command consists of the keywords "CREATE INDEX" followed by the name of the new index, the keyword "ON", the name of a previously created table that is to be indexed, and a parenthesized list of names of columns in the table that are used for the index key. Each column name can be followed by one of the "ASC" or "DESC" keywords to indicate sort order, but the sort order is ignored in the current implementation. Sorting is always done in ascending order.

The COLLATE clause following each column name defines a collating sequence used for text entires in that column. The default collating sequence is the collating sequence defined for that column in the CREATE TABLE statement. Or if no collating sequence is otherwise defined, the built-in BINARY collating sequence is used.

There are no arbitrary limits on the number of indices that can be attached to a single table, nor on the number of columns in an index.

If the UNIQUE keyword appears between CREATE and INDEX then duplicate index entries are not allowed. Any attempt to insert a duplicate entry will result in an error.

The exact text of each CREATE INDEX statement is stored in the sqlite_master or sqlite_temp_master table, depending on whether the table being indexed is temporary. Every time the database is opened, all CREATE INDEX statements are read from the sqlite_master table and used to regenerate SQLite's internal representation of the index layout.

If the optional IF NOT EXISTS clause is present and another index with the same name aleady exists, then this command becomes a no-op.

Indexes are removed with the DROP INDEX command.


CREATE TABLE

sql-command ::= CREATE [TEMP | TEMPORARY] TABLE [IF NOT EXISTS] table-name (
    
column-def [, column-def]*
    
[, constraint]*
)
sql-command ::= CREATE [TEMP | TEMPORARY] TABLE [database-name.] table-name AS select-statement
column-def ::= name [type] [[CONSTRAINT name] column-constraint]*
type ::= typename |
typename ( number ) |
typename ( number , number )
column-constraint ::= NOT NULL [ conflict-clause ] |
PRIMARY KEY
[sort-order] [ conflict-clause ] [AUTOINCREMENT] |
UNIQUE
[ conflict-clause ] |
CHECK (
expr ) |
DEFAULT
value |
COLLATE
collation-name
constraint ::= PRIMARY KEY ( column-list ) [ conflict-clause ] |
UNIQUE (
column-list ) [ conflict-clause ] |
CHECK (
expr )
conflict-clause ::= ON CONFLICT conflict-algorithm

A CREATE TABLE statement is basically the keywords "CREATE TABLE" followed by the name of a new table and a parenthesized list of column definitions and constraints. The table name can be either an identifier or a string. Tables names that begin with "sqlite_" are reserved for use by the engine.

Each column definition is the name of the column followed by the datatype for that column, then one or more optional column constraints. The datatype for the column does not restrict what data may be put in that column. See Datatypes In SQLite Version 3 for additional information. The UNIQUE constraint causes an index to be created on the specified columns. This index must contain unique keys. The COLLATE clause specifies what text collating function to use when comparing text entries for the column. The built-in BINARY collating function is used by default.

The DEFAULT constraint specifies a default value to use when doing an INSERT. The value may be NULL, a string constant or a number. Starting with version 3.1.0, the default value may also be one of the special case-independant keywords CURRENT_TIME, CURRENT_DATE or CURRENT_TIMESTAMP. If the value is NULL, a string constant or number, it is literally inserted into the column whenever an INSERT statement that does not specify a value for the column is executed. If the value is CURRENT_TIME, CURRENT_DATE or CURRENT_TIMESTAMP, then the current UTC date and/or time is inserted into the columns. For CURRENT_TIME, the format is HH:MM:SS. For CURRENT_DATE, YYYY-MM-DD. The format for CURRENT_TIMESTAMP is "YYYY-MM-DD HH:MM:SS".

Specifying a PRIMARY KEY normally just creates a UNIQUE index on the corresponding columns. However, if primary key is on a single column that has datatype INTEGER, then that column is used internally as the actual key of the B-Tree for the table. This means that the column may only hold unique integer values. (Except for this one case, SQLite ignores the datatype specification of columns and allows any kind of data to be put in a column regardless of its declared datatype.) If a table does not have an INTEGER PRIMARY KEY column, then the B-Tree key will be a automatically generated integer. The B-Tree key for a row can always be accessed using one of the special names "ROWID", "OID", or "_ROWID_". This is true regardless of whether or not there is an INTEGER PRIMARY KEY. An INTEGER PRIMARY KEY column man also include the keyword AUTOINCREMENT. The AUTOINCREMENT keyword modified the way that B-Tree keys are automatically generated. Additional detail on automatic B-Tree key generation is available separately.

If the "TEMP" or "TEMPORARY" keyword occurs in between "CREATE" and "TABLE" then the table that is created is only visible within that same database connection and is automatically deleted when the database connection is closed. Any indices created on a temporary table are also temporary. Temporary tables and indices are stored in a separate file distinct from the main database file.

If a <database-name> is specified, then the table is created in the named database. It is an error to specify both a <database-name> and the TEMP keyword, unless the <database-name> is "temp". If no database name is specified, and the TEMP keyword is not present, the table is created in the main database.

The optional conflict-clause following each constraint allows the specification of an alternative default constraint conflict resolution algorithm for that constraint. The default is abort ABORT. Different constraints within the same table may have different default conflict resolution algorithms. If an COPY, INSERT, or UPDATE command specifies a different conflict resolution algorithm, then that algorithm is used in place of the default algorithm specified in the CREATE TABLE statement. See the section titled ON CONFLICT for additional information.

CHECK constraints are supported as of version 3.3.0. Prior to version 3.3.0, CHECK constraints were parsed but not enforced.

There are no arbitrary limits on the number of columns or on the number of constraints in a table. The total amount of data in a single row is limited to about 1 megabytes in version 2.8. In version 3.0 there is no arbitrary limit on the amount of data in a row.

The CREATE TABLE AS form defines the table to be the result set of a query. The names of the table columns are the names of the columns in the result.

The exact text of each CREATE TABLE statement is stored in the sqlite_master table. Every time the database is opened, all CREATE TABLE statements are read from the sqlite_master table and used to regenerate SQLite's internal representation of the table layout. If the original command was a CREATE TABLE AS then then an equivalent CREATE TABLE statement is synthesized and store in sqlite_master in place of the original command. The text of CREATE TEMPORARY TABLE statements are stored in the sqlite_temp_master table.

If the optional IF NOT EXISTS clause is present and another table with the same name aleady exists, then this command becomes a no-op.

Tables are removed using the DROP TABLE statement.


CREATE TRIGGER

sql-statement ::= CREATE [TEMP | TEMPORARY] TRIGGER trigger-name [ BEFORE | AFTER ]
database-event ON [database-name .] table-name
trigger-action
sql-statement ::= CREATE [TEMP | TEMPORARY] TRIGGER trigger-name INSTEAD OF
database-event ON [database-name .] view-name
trigger-action
database-event ::= DELETE |
INSERT
|
UPDATE
|
UPDATE OF
column-list
trigger-action ::= [ FOR EACH ROW | FOR EACH STATEMENT ] [ WHEN expression ]
BEGIN
    
trigger-step ; [ trigger-step ; ]*
END
trigger-step ::= update-statement | insert-statement |
delete-statement | select-statement

The CREATE TRIGGER statement is used to add triggers to the database schema. Triggers are database operations (the trigger-action) that are automatically performed when a specified database event (the database-event) occurs.

A trigger may be specified to fire whenever a DELETE, INSERT or UPDATE of a particular database table occurs, or whenever an UPDATE of one or more specified columns of a table are updated.

At this time SQLite supports only FOR EACH ROW triggers, not FOR EACH STATEMENT triggers. Hence explicitly specifying FOR EACH ROW is optional. FOR EACH ROW implies that the SQL statements specified as trigger-steps may be executed (depending on the WHEN clause) for each database row being inserted, updated or deleted by the statement causing the trigger to fire.

Both the WHEN clause and the trigger-steps may access elements of the row being inserted, deleted or updated using references of the form "NEW.column-name" and "OLD.column-name", where column-name is the name of a column from the table that the trigger is associated with. OLD and NEW references may only be used in triggers on trigger-events for which they are relevant, as follows:

INSERT NEW references are valid
UPDATE NEW and OLD references are valid
DELETE OLD references are valid

If a WHEN clause is supplied, the SQL statements specified as trigger-steps are only executed for rows for which the WHEN clause is true. If no WHEN clause is supplied, the SQL statements are executed for all rows.

The specified trigger-time determines when the trigger-steps will be executed relative to the insertion, modification or removal of the associated row.

An ON CONFLICT clause may be specified as part of an UPDATE or INSERT trigger-step. However if an ON CONFLICT clause is specified as part of the statement causing the trigger to fire, then this conflict handling policy is used instead.

Triggers are automatically dropped when the table that they are associated with is dropped.

Triggers may be created on views, as well as ordinary tables, by specifying INSTEAD OF in the CREATE TRIGGER statement. If one or more ON INSERT, ON DELETE or ON UPDATE triggers are defined on a view, then it is not an error to execute an INSERT, DELETE or UPDATE statement on the view, respectively. Thereafter, executing an INSERT, DELETE or UPDATE on the view causes the associated triggers to fire. The real tables underlying the view are not modified (except possibly explicitly, by a trigger program).

Example:

Assuming that customer records are stored in the "customers" table, and that order records are stored in the "orders" table, the following trigger ensures that all associated orders are redirected when a customer changes his or her address:

CREATE TRIGGER update_customer_address UPDATE OF address ON customers 
  BEGIN
    UPDATE orders SET address = new.address WHERE customer_name = old.name;
  END;

With this trigger installed, executing the statement:

UPDATE customers SET address = '1 Main St.' WHERE name = 'Jack Jones';

causes the following to be automatically executed:

UPDATE orders SET address = '1 Main St.' WHERE customer_name = 'Jack Jones';

Note that currently, triggers may behave oddly when created on tables with INTEGER PRIMARY KEY fields. If a BEFORE trigger program modifies the INTEGER PRIMARY KEY field of a row that will be subsequently updated by the statement that causes the trigger to fire, then the update may not occur. The workaround is to declare the table with a PRIMARY KEY column instead of an INTEGER PRIMARY KEY column.

A special SQL function RAISE() may be used within a trigger-program, with the following syntax

raise-function ::= RAISE ( ABORT, error-message ) |
RAISE ( FAIL,
error-message ) |
RAISE ( ROLLBACK,
error-message ) |
RAISE ( IGNORE )

When one of the first three forms is called during trigger-program execution, the specified ON CONFLICT processing is performed (either ABORT, FAIL or ROLLBACK) and the current query terminates. An error code of SQLITE_CONSTRAINT is returned to the user, along with the specified error message.

When RAISE(IGNORE) is called, the remainder of the current trigger program, the statement that caused the trigger program to execute and any subsequent trigger programs that would of been executed are abandoned. No database changes are rolled back. If the statement that caused the trigger program to execute is itself part of a trigger program, then that trigger program resumes execution at the beginning of the next step.

Triggers are removed using the DROP TRIGGER statement.


CREATE VIEW

sql-command ::= CREATE [TEMP | TEMPORARY] VIEW [database-name.] view-name AS select-statement

The CREATE VIEW command assigns a name to a pre-packaged SELECT statement. Once the view is created, it can be used in the FROM clause of another SELECT in place of a table name.

If the "TEMP" or "TEMPORARY" keyword occurs in between "CREATE" and "VIEW" then the view that is created is only visible to the process that opened the database and is automatically deleted when the database is closed.

If a <database-name> is specified, then the view is created in the named database. It is an error to specify both a <database-name> and the TEMP keyword, unless the <database-name> is "temp". If no database name is specified, and the TEMP keyword is not present, the table is created in the main database.

You cannot COPY, DELETE, INSERT or UPDATE a view. Views are read-only in SQLite. However, in many cases you can use a TRIGGER on the view to accomplish the same thing. Views are removed with the DROP VIEW command.


DELETE

sql-statement ::= DELETE FROM [database-name .] table-name [WHERE expr]

The DELETE command is used to remove records from a table. The command consists of the "DELETE FROM" keywords followed by the name of the table from which records are to be removed.

Without a WHERE clause, all rows of the table are removed. If a WHERE clause is supplied, then only those rows that match the expression are removed.


DETACH DATABASE

sql-command ::= DETACH [DATABASE] database-name

This statement detaches an additional database connection previously attached using the ATTACH DATABASE statement. It is possible to have the same database file attached multiple times using different names, and detaching one connection to a file will leave the others intact.

This statement will fail if SQLite is in the middle of a transaction.


DROP INDEX

sql-command ::= DROP INDEX [IF EXISTS] [database-name .] index-name

The DROP INDEX statement removes an index added with the CREATE INDEX statement. The index named is completely removed from the disk. The only way to recover the index is to reenter the appropriate CREATE INDEX command.

The DROP INDEX statement does not reduce the size of the database file in the default mode. Empty space in the database is retained for later INSERTs. To remove free space in the database, use the VACUUM command. If AUTOVACUUM mode is enabled for a database then space will be freed automatically by DROP INDEX.


DROP TABLE

sql-command ::= DROP TABLE [IF EXISTS] [database-name.] table-name

The DROP TABLE statement removes a table added with the CREATE TABLE statement. The name specified is the table name. It is completely removed from the database schema and the disk file. The table can not be recovered. All indices associated with the table are also deleted.

The DROP TABLE statement does not reduce the size of the database file in the default mode. Empty space in the database is retained for later INSERTs. To remove free space in the database, use the VACUUM command. If AUTOVACUUM mode is enabled for a database then space will be freed automatically by DROP TABLE.

The optional IF EXISTS clause suppresses the error that would normally result if the table does not exist.


DROP TRIGGER

sql-statement ::= DROP TRIGGER [database-name .] trigger-name

The DROP TRIGGER statement removes a trigger created by the CREATE TRIGGER statement. The trigger is deleted from the database schema. Note that triggers are automatically dropped when the associated table is dropped.


DROP VIEW

sql-command ::= DROP VIEW view-name

The DROP VIEW statement removes a view created by the CREATE VIEW statement. The name specified is the view name. It is removed from the database schema, but no actual data in the underlying base tables is modified.


EXPLAIN

sql-statement ::= EXPLAIN sql-statement

The EXPLAIN command modifier is a non-standard extension. The idea comes from a similar command found in PostgreSQL, but the operation is completely different.

If the EXPLAIN keyword appears before any other SQLite SQL command then instead of actually executing the command, the SQLite library will report back the sequence of virtual machine instructions it would have used to execute the command had the EXPLAIN keyword not been present. For additional information about virtual machine instructions see the architecture description or the documentation on available opcodes for the virtual machine.


expression

expr ::= expr binary-op expr |
expr [NOT] like-op expr [ESCAPE expr] |
unary-op expr |
(
expr ) |
column-name |
table-name . column-name |
database-name . table-name . column-name |
literal-value |
parameter |
function-name ( expr-list | * ) |
expr ISNULL |
expr NOTNULL |
expr [NOT] BETWEEN expr AND expr |
expr [NOT] IN ( value-list ) |
expr [NOT] IN ( select-statement ) |
expr [NOT] IN [database-name .] table-name |
[EXISTS] ( select-statement ) |
CASE
[expr] ( WHEN expr THEN expr )+ [ELSE expr] END |
CAST (
expr AS type )
like-op ::= LIKE | GLOB | REGEXP

This section is different from the others. Most other sections of this document talks about a particular SQL command. This section does not talk about a standalone command but about "expressions" which are subcomponents of most other commands.

SQLite understands the following binary operators, in order from highest to lowest precedence:

||
*    /    %
+    -
<<   >>   &    |
<    <=   >    >=
=    ==   !=   <>   IN
AND   
OR

Supported unary operators are these:

-    +    !    ~    NOT

Note that there are two variations of the equals and not equals operators. Equals can be either = or ==. The non-equals operator can be either != or <>. The || operator is "concatenate" - it joins together the two strings of its operands. The operator % outputs the remainder of its left operand modulo its right operand.

The result of any binary operator is a numeric value, except for the || concatenation operator which gives a string result.

A literal value is an integer number or a floating point number. Scientific notation is supported. The "." character is always used as the decimal point even if the locale setting specifies "," for this role - the use of "," for the decimal point would result in syntactic ambiguity. A string constant is formed by enclosing the string in single quotes ('). A single quote within the string can be encoded by putting two single quotes in a row - as in Pascal. C-style escapes using the backslash character are not supported because they are not standard SQL. BLOB literals are string literals containing hexadecimal data and preceded by a single "x" or "X" character. For example:

X'53514697465'

A literal value can also be the token "NULL".

A parameter specifies a placeholder in the expression for a literal value that is filled in at runtime using the sqlite3_bind API. Parameters can take several forms:

?NNN A question mark followed by a number NNN holds a spot for the NNN-th parameter. NNN must be between 1 and 999.
? A question mark that is not followed by a number holds a spot for the next unused parameter.
:AAAA A colon followed by an identifier name holds a spot for a named parameter with the name AAAA. Named parameters are also numbered. The number assigned is the next unused number. To avoid confusion, it is best to avoid mixing named and numbered parameters.
$AAAA A dollar-sign followed by an identifier name also holds a spot for a named parameter with the name AAAA. The identifier name in this case can include one or more occurances of "::" and a suffix enclosed in "(...)" containing any text at all. This syntax is the form of a variable name in the Tcl programming language.

Parameters that are not assigned values using sqlite3_bind are treated as NULL.

The LIKE operator does a pattern matching comparison. The operand to the right contains the pattern, the left hand operand contains the string to match against the pattern. A percent symbol % in the pattern matches any sequence of zero or more characters in the string. An underscore _ in the pattern matches any single character in the string. Any other character matches itself or it's lower/upper case equivalent (i.e. case-insensitive matching). (A bug: SQLite only understands upper/lower case for 7-bit Latin characters. Hence the LIKE operator is case sensitive for 8-bit iso8859 characters or UTF-8 characters. For example, the expression 'a' LIKE 'A' is TRUE but 'æ' LIKE 'Æ' is FALSE.).

If the optional ESCAPE clause is present, then the expression following the ESCAPE keyword must evaluate to a string consisting of a single character. This character may be used in the LIKE pattern to include literal percent or underscore characters. The escape character followed by a percent symbol, underscore or itself matches a literal percent symbol, underscore or escape character in the string, respectively. The infix LIKE operator is implemented by calling the user function like(X,Y).

The LIKE operator is not case sensitive and will match upper case characters on one side against lower case characters on the other. (A bug: SQLite only understands upper/lower case for 7-bit Latin characters. Hence the LIKE operator is case sensitive for 8-bit iso8859 characters or UTF-8 characters. For example, the expression 'a' LIKE 'A' is TRUE but 'æ' LIKE 'Æ' is FALSE.).

The infix LIKE operator is implemented by calling the user function like(X,Y). If an ESCAPE clause is present, it adds a third parameter to the function call. If the functionality of LIKE can be overridden by defining an alternative implementation of the like() SQL function.

The GLOB operator is similar to LIKE but uses the Unix file globbing syntax for its wildcards. Also, GLOB is case sensitive, unlike LIKE. Both GLOB and LIKE may be preceded by the NOT keyword to invert the sense of the test. The infix GLOB operator is implemented by calling the user function glob(X,Y) and can be modified by overriding that function.

The REGEXP operator is a special syntax for the regexp() user function. No regexp() user function is defined by default and so use of the REGEXP operator will normally result in an error message. If a user-defined function named "regexp" is defined at run-time, that function will be called in order to implement the REGEXP operator.

A column name can be any of the names defined in the CREATE TABLE statement or one of the following special identifiers: "ROWID", "OID", or "_ROWID_". These special identifiers all describe the unique random integer key (the "row key") associated with every row of every table. The special identifiers only refer to the row key if the CREATE TABLE statement does not define a real column with the same name. Row keys act like read-only columns. A row key can be used anywhere a regular column can be used, except that you cannot change the value of a row key in an UPDATE or INSERT statement. "SELECT * ..." does not return the row key.

SELECT statements can appear in expressions as either the right-hand operand of the IN operator, as a scalar quantity, or as the operand of an EXISTS operator. As a scalar quantity or the operand of an IN operator, the SELECT should have only a single column in its result. Compound SELECTs (connected with keywords like UNION or EXCEPT) are allowed. With the EXISTS operator, the columns in the result set of the SELECT are ignored and the expression returns TRUE if one or more rows exist and FALSE if the result set is empty. If no terms in the SELECT expression refer to value in the containing query, then the expression is evaluated once prior to any other processing and the result is reused as necessary. If the SELECT expression does contain variables from the outer query, then the SELECT is reevaluated every time it is needed.

When a SELECT is the right operand of the IN operator, the IN operator returns TRUE if the result of the left operand is any of the values generated by the select. The IN operator may be preceded by the NOT keyword to invert the sense of the test.

When a SELECT appears within an expression but is not the right operand of an IN operator, then the first row of the result of the SELECT becomes the value used in the expression. If the SELECT yields more than one result row, all rows after the first are ignored. If the SELECT yields no rows, then the value of the SELECT is NULL.

A CAST expression changes the datatype of the into the type specified by <type>. <type> can be any non-empty type name that is valid for the type in a column definition of a CREATE TABLE statement.

Both simple and aggregate functions are supported. A simple function can be used in any expression. Simple functions return a result immediately based on their inputs. Aggregate functions may only be used in a SELECT statement. Aggregate functions compute their result across all rows of the result set.

The functions shown below are available by default. Additional functions may be written in C and added to the database engine using the sqlite3_create_function() API.

abs(X) Return the absolute value of argument X.
coalesce(X,Y,...) Return a copy of the first non-NULL argument. If all arguments are NULL then NULL is returned. There must be at least 2 arguments.
glob(X,Y) This function is used to implement the "X GLOB Y" syntax of SQLite. The sqlite3_create_function() interface can be used to override this function and thereby change the operation of the GLOB operator.
ifnull(X,Y) Return a copy of the first non-NULL argument. If both arguments are NULL then NULL is returned. This behaves the same as coalesce() above.
last_insert_rowid() Return the ROWID of the last row insert from this connection to the database. This is the same value that would be returned from the sqlite_last_insert_rowid() API function.
length(X) Return the string length of X in characters. If SQLite is configured to support UTF-8, then the number of UTF-8 characters is returned, not the number of bytes.
like(X,Y [,Z]) This function is used to implement the "X LIKE Y [ESCAPE Z]" syntax of SQL. If the optional ESCAPE clause is present, then the user-function is invoked with three arguments. Otherwise, it is invoked with two arguments only. The sqlite_create_function() interface can be used to override this function and thereby change the operation of the LIKE operator. When doing this, it may be important to override both the two and three argument versions of the like() function. Otherwise, different code may be called to implement the LIKE operator depending on whether or not an ESCAPE clause was specified.
lower(X) Return a copy of string X will all characters converted to lower case. The C library tolower() routine is used for the conversion, which means that this function might not work correctly on UTF-8 characters.
max(X,Y,...) Return the argument with the maximum value. Arguments may be strings in addition to numbers. The maximum value is determined by the usual sort order. Note that max() is a simple function when it has 2 or more arguments but converts to an aggregate function if given only a single argument.
min(X,Y,...) Return the argument with the minimum value. Arguments may be strings in addition to numbers. The minimum value is determined by the usual sort order. Note that min() is a simple function when it has 2 or more arguments but converts to an aggregate function if given only a single argument.
nullif(X,Y) Return the first argument if the arguments are different, otherwise return NULL.
quote(X) This routine returns a string which is the value of its argument suitable for inclusion into another SQL statement. Strings are surrounded by single-quotes with escapes on interior quotes as needed. BLOBs are encoded as hexadecimal literals. The current implementation of VACUUM uses this function. The function is also useful when writing triggers to implement undo/redo functionality.
random(*) Return a random integer between -2147483648 and +2147483647.
round(X)
round(X,Y)
Round off the number X to Y digits to the right of the decimal point. If the Y argument is omitted, 0 is assumed.
soundex(X) Compute the soundex encoding of the string X. The string "?000" is returned if the argument is NULL. This function is omitted from SQLite by default. It is only available the -DSQLITE_SOUNDEX=1 compiler option is used when SQLite is built.
sqlite_version(*) Return the version string for the SQLite library that is running. Example: "2.8.0"
substr(X,Y,Z) Return a substring of input string X that begins with the Y-th character and which is Z characters long. The left-most character of X is number 1. If Y is negative the the first character of the substring is found by counting from the right rather than the left. If SQLite is configured to support UTF-8, then characters indices refer to actual UTF-8 characters, not bytes.
typeof(X) Return the type of the expression X. The only return values are "null", "integer", "real", "text", and "blob". SQLite's type handling is explained in Datatypes in SQLite Version 3.
upper(X) Return a copy of input string X converted to all upper-case letters. The implementation of this function uses the C library routine toupper() which means it may not work correctly on UTF-8 strings.

The aggregate functions shown below are available by default. Additional aggregate functions written in C may be added using the sqlite3_create_function() API.

In any aggregate function that takes a single argument, that argument can be preceeded by the keyword DISTINCT. In such cases, duplicate elements are filtered before being passed into the aggregate function. For example, the function "count(distinct X)" will return the number of distinct values of column X instead of the total number of non-null values in column X.

avg(X) Return the average value of all non-NULL X within a group. String and BLOB values that do not look like numbers are interpreted as 0. The result of avg() is always a floating point value even if all inputs are integers.

count(X)
count(*)
The first form return a count of the number of times that X is not NULL in a group. The second form (with no argument) returns the total number of rows in the group.
max(X) Return the maximum value of all values in the group. The usual sort order is used to determine the maximum.
min(X) Return the minimum non-NULL value of all values in the group. The usual sort order is used to determine the minimum. NULL is only returned if all values in the group are NULL.
sum(X)
total(X)
Return the numeric sum of all non-NULL values in the group. If there are no non-NULL input rows then sum() returns NULL but total() returns 0.0. NULL is not normally a helpful result for the sum of no rows but the SQL standard requires it and most other SQL database engines implement sum() that way so SQLite does it in the same way in order to be compatible. The non-standard total() function is provided as a convenient way to work around this design problem in the SQL language.

The result of total() is always a floating point value. The result of sum() is an integer value if all non-NULL inputs are integers. If any input to sum() is neither an integer or a NULL then sum() returns a floating point value which might be an approximation to the true sum.

Sum() will throw an "integer overflow" exception if all inputs are integers or NULL and an integer overflow occurs at any point during the computation. Total() never throws an exception.


INSERT

sql-statement ::= INSERT [OR conflict-algorithm] INTO [database-name .] table-name [(column-list)] VALUES(value-list) |
INSERT
[OR conflict-algorithm] INTO [database-name .] table-name [(column-list)] select-statement

The INSERT statement comes in two basic forms. The first form (with the "VALUES" keyword) creates a single new row in an existing table. If no column-list is specified then the number of values must be the same as the number of columns in the table. If a column-list is specified, then the number of values must match the number of specified columns. Columns of the table that do not appear in the column list are filled with the default value, or with NULL if not default value is specified.

The second form of the INSERT statement takes it data from a SELECT statement. The number of columns in the result of the SELECT must exactly match the number of columns in the table if no column list is specified, or it must match the number of columns name in the column list. A new entry is made in the table for every row of the SELECT result. The SELECT may be simple or compound. If the SELECT statement has an ORDER BY clause, the ORDER BY is ignored.

The optional conflict-clause allows the specification of an alternative constraint conflict resolution algorithm to use during this one command. See the section titled ON CONFLICT for additional information. For compatibility with MySQL, the parser allows the use of the single keyword REPLACE as an alias for "INSERT OR REPLACE".


ON CONFLICT clause

conflict-clause ::= ON CONFLICT conflict-algorithm
conflict-algorithm ::= ROLLBACK | ABORT | FAIL | IGNORE | REPLACE

The ON CONFLICT clause is not a separate SQL command. It is a non-standard clause that can appear in many other SQL commands. It is given its own section in this document because it is not part of standard SQL and therefore might not be familiar.

The syntax for the ON CONFLICT clause is as shown above for the CREATE TABLE command. For the INSERT and UPDATE commands, the keywords "ON CONFLICT" are replaced by "OR", to make the syntax seem more natural. For example, instead of "INSERT ON CONFLICT IGNORE" we have "INSERT OR IGNORE". The keywords change but the meaning of the clause is the same either way.

The ON CONFLICT clause specifies an algorithm used to resolve constraint conflicts. There are five choices: ROLLBACK, ABORT, FAIL, IGNORE, and REPLACE. The default algorithm is ABORT. This is what they mean:

ROLLBACK

When a constraint violation occurs, an immediate ROLLBACK occurs, thus ending the current transaction, and the command aborts with a return code of SQLITE_CONSTRAINT. If no transaction is active (other than the implied transaction that is created on every command) then this algorithm works the same as ABORT.

ABORT

When a constraint violation occurs, the command backs out any prior changes it might have made and aborts with a return code of SQLITE_CONSTRAINT. But no ROLLBACK is executed so changes from prior commands within the same transaction are preserved. This is the default behavior.

FAIL

When a constraint violation occurs, the command aborts with a return code SQLITE_CONSTRAINT. But any changes to the database that the command made prior to encountering the constraint violation are preserved and are not backed out. For example, if an UPDATE statement encountered a constraint violation on the 100th row that it attempts to update, then the first 99 row changes are preserved but changes to rows 100 and beyond never occur.

IGNORE

When a constraint violation occurs, the one row that contains the constraint violation is not inserted or changed. But the command continues executing normally. Other rows before and after the row that contained the constraint violation continue to be inserted or updated normally. No error is returned.

REPLACE

When a UNIQUE constraint violation occurs, the pre-existing rows that are causing the constraint violation are removed prior to inserting or updating the current row. Thus the insert or update always occurs. The command continues executing normally. No error is returned. If a NOT NULL constraint violation occurs, the NULL value is replaced by the default value for that column. If the column has no default value, then the ABORT algorithm is used. If a CHECK constraint violation occurs then the IGNORE algorithm is used.

When this conflict resolution strategy deletes rows in order to satisfy a constraint, it does not invoke delete triggers on those rows. This behavior might change in a future release.

The algorithm specified in the OR clause of a INSERT or UPDATE overrides any algorithm specified in a CREATE TABLE. If no algorithm is specified anywhere, the ABORT algorithm is used.


REINDEX

sql-statement ::= REINDEX collation name
sql-statement ::= REINDEX [database-name .] table/index-name

The REINDEX command is used to delete and recreate indices from scratch. This is useful when the definition of a collation sequence has changed.

In the first form, all indices in all attached databases that use the named collation sequence are recreated. In the second form, if [database-name.]table/index-name identifies a table, then all indices associated with the table are rebuilt. If an index is identified, then only this specific index is deleted and recreated.

If no database-name is specified and there exists both a table or index and a collation sequence of the specified name, then indices associated with the collation sequence only are reconstructed. This ambiguity may be dispelled by always specifying a database-name when reindexing a specific table or index.


REPLACE

sql-statement ::= REPLACE INTO [database-name .] table-name [( column-list )] VALUES ( value-list ) |
REPLACE INTO
[database-name .] table-name [( column-list )] select-statement

The REPLACE command is an alias for the "INSERT OR REPLACE" variant of the INSERT command. This alias is provided for compatibility with MySQL. See the INSERT command documentation for additional information.


SELECT

sql-statement ::= SELECT [ALL | DISTINCT] result [FROM table-list]
[WHERE expr]
[GROUP BY expr-list]
[HAVING expr]
[compound-op select]*
[ORDER BY sort-expr-list]
[LIMIT integer [( OFFSET | , ) integer]]
result ::= result-column [, result-column]*
result-column ::= * | table-name . * | expr [ [AS] string ]
table-list ::= table [join-op table join-args]*
table ::= table-name [AS alias] |
(
select ) [AS alias]
join-op ::= , | [NATURAL] [LEFT | RIGHT | FULL] [OUTER | INNER | CROSS] JOIN
join-args ::= [ON expr] [USING ( id-list )]
sort-expr-list ::= expr [sort-order] [, expr [sort-order]]*
sort-order ::= [ COLLATE collation-name ] [ ASC | DESC ]
compound_op ::= UNION | UNION ALL | INTERSECT | EXCEPT

The SELECT statement is used to query the database. The result of a SELECT is zero or more rows of data where each row has a fixed number of columns. The number of columns in the result is specified by the expression list in between the SELECT and FROM keywords. Any arbitrary expression can be used as a result. If a result expression is * then all columns of all tables are substituted for that one expression. If the expression is the name of a table followed by .* then the result is all columns in that one table.

The DISTINCT keyword causes a subset of result rows to be returned, in which each result row is different. NULL values are not treated as distinct from each other. The default behavior is that all result rows be returned, which can be made explicit with the keyword ALL.

The query is executed against one or more tables specified after the FROM keyword. If multiple tables names are separated by commas, then the query is against the cross join of the various tables. The full SQL-92 join syntax can also be used to specify joins. A sub-query in parentheses may be substituted for any table name in the FROM clause. The entire FROM clause may be omitted, in which case the result is a single row consisting of the values of the expression list.

The WHERE clause can be used to limit the number of rows over which the query operates.

The GROUP BY clauses causes one or more rows of the result to be combined into a single row of output. This is especially useful when the result contains aggregate functions. The expressions in the GROUP BY clause do not have to be expressions that appear in the result. The HAVING clause is similar to WHERE except that HAVING applies after grouping has occurred. The HAVING expression may refer to values, even aggregate functions, that are not in the result.

The ORDER BY clause causes the output rows to be sorted. The argument to ORDER BY is a list of expressions that are used as the key for the sort. The expressions do not have to be part of the result for a simple SELECT, but in a compound SELECT each sort expression must exactly match one of the result columns. Each sort expression may be optionally followed by a COLLATE keyword and the name of a collating function used for ordering text and/or keywords ASC or DESC to specify the sort order.

The LIMIT clause places an upper bound on the number of rows returned in the result. A negative LIMIT indicates no upper bound. The optional OFFSET following LIMIT specifies how many rows to skip at the beginning of the result set. In a compound query, the LIMIT clause may only appear on the final SELECT statement. The limit is applied to the entire query not to the individual SELECT statement to which it is attached. Note that if the OFFSET keyword is used in the LIMIT clause, then the limit is the first number and the offset is the second number. If a comma is used instead of the OFFSET keyword, then the offset is the first number and the limit is the second number. This seeming contradition is intentional - it maximizes compatibility with legacy SQL database systems.

A compound SELECT is formed from two or more simple SELECTs connected by one of the operators UNION, UNION ALL, INTERSECT, or EXCEPT. In a compound SELECT, all the constituent SELECTs must specify the same number of result columns. There may be only a single ORDER BY clause at the end of the compound SELECT. The UNION and UNION ALL operators combine the results of the SELECTs to the right and left into a single big table. The difference is that in UNION all result rows are distinct where in UNION ALL there may be duplicates. The INTERSECT operator takes the intersection of the results of the left and right SELECTs. EXCEPT takes the result of left SELECT after removing the results of the right SELECT. When three or more SELECTs are connected into a compound, they group from left to right.


UPDATE

sql-statement ::= UPDATE [ OR conflict-algorithm ] [database-name .] table-name
SET
assignment [, assignment]*
[WHERE expr]
assignment ::= column-name = expr

The UPDATE statement is used to change the value of columns in selected rows of a table. Each assignment in an UPDATE specifies a column name to the left of the equals sign and an arbitrary expression to the right. The expressions may use the values of other columns. All expressions are evaluated before any assignments are made. A WHERE clause can be used to restrict which rows are updated.

The optional conflict-clause allows the specification of an alternative constraint conflict resolution algorithm to use during this one command. See the section titled ON CONFLICT for additional information.


VACUUM

sql-statement ::= VACUUM [index-or-table-name]

The VACUUM command is an SQLite extension modeled after a similar command found in PostgreSQL. If VACUUM is invoked with the name of a table or index then it is suppose to clean up the named table or index. In version 1.0 of SQLite, the VACUUM command would invoke gdbm_reorganize() to clean up the backend database file.

VACUUM became a no-op when the GDBM backend was removed from SQLITE in version 2.0.0. VACUUM was reimplemented in version 2.8.1. The index or table name argument is now ignored.

When an object (table, index, or trigger) is dropped from the database, it leaves behind empty space. This makes the database file larger than it needs to be, but can speed up inserts. In time inserts and deletes can leave the database file structure fragmented, which slows down disk access to the database contents. The VACUUM command cleans the main database by copying its contents to a temporary database file and reloading the original database file from the copy. This eliminates free pages, aligns table data to be contiguous, and otherwise cleans up the database file structure. It is not possible to perform the same process on an attached database file.

This command will fail if there is an active transaction. This command has no effect on an in-memory database.

As of SQLite version 3.1, an alternative to using the VACUUM command is auto-vacuum mode, enabled using the auto_vacuum pragma.


PRAGMA command syntax

sql-statement ::= PRAGMA name [= value] |
PRAGMA
function(arg)

The pragmas that take an integer value also accept symbolic names. The strings "on", "true", and "yes" are equivalent to 1. The strings "off", "false", and "no" are equivalent to 0. These strings are case- insensitive, and do not require quotes. An unrecognized string will be treated as 1, and will not generate an error. When the value is returned it is as an integer.


The PRAGMA command is a special command used to modify the operation of the SQLite library or to query the library for internal (non-table) data. The PRAGMA command is issued using the same interface as other SQLite commands (e.g. SELECT, INSERT) but is different in the following important respects:

  • Specific pragma statements may be removed and others added in future releases of SQLite. Use with caution!
  • No error messages are generated if an unknown pragma is issued. Unknown pragmas are simply ignored. This means if there is a typo in a pragma statement the library does not inform the user of the fact.
  • Some pragmas take effect during the SQL compilation stage, not the execution stage. This means if using the C-language sqlite3_compile(), sqlite3_step(), sqlite3_finalize() API (or similar in a wrapper interface), the pragma may be applied to the library during the sqlite3_compile() call.
  • The pragma command is unlikely to be compatible with any other SQL engine.

The available pragmas fall into four basic categories:


Pragmas to modify library operation

  • PRAGMA auto_vacuum;
    PRAGMA auto_vacuum =
    0 | 1;

    Query or set the auto-vacuum flag in the database.

    Normally, when a transaction that deletes data from a database is committed, the database file remains the same size. Unused database file pages are marked as such and reused later on, when data is inserted into the database. In this mode the VACUUM command is used to reclaim unused space.

    When the auto-vacuum flag is set, the database file shrinks when a transaction that deletes data is committed (The VACUUM command is not useful in a database with the auto-vacuum flag set). To support this functionality the database stores extra information internally, resulting in slightly larger database files than would otherwise be possible.

    It is only possible to modify the value of the auto-vacuum flag before any tables have been created in the database. No error message is returned if an attempt to modify the auto-vacuum flag is made after one or more tables have been created.

  • PRAGMA cache_size;
    PRAGMA cache_size =
    Number-of-pages;

    Query or change the maximum number of database disk pages that SQLite will hold in memory at once. Each page uses about 1.5K of memory. The default cache size is 2000. If you are doing UPDATEs or DELETEs that change many rows of a database and you do not mind if SQLite uses more memory, you can increase the cache size for a possible speed improvement.

    When you change the cache size using the cache_size pragma, the change only endures for the current session. The cache size reverts to the default value when the database is closed and reopened. Use the default_cache_size pragma to check the cache size permanently.

  • PRAGMA case_sensitive_like;
    PRAGMA case_sensitive_like =
    0 | 1;

    The default behavior of the LIKE operator is to ignore case for latin1 characters. Hence, by default 'a' LIKE 'A' is true. The case_sensitive_like pragma can be turned on to change this behavior. When case_sensitive_like is enabled, 'a' LIKE 'A' is false but 'a' LIKE 'a' is still true.

  • PRAGMA count_changes;
    PRAGMA count_changes =
    0 | 1;

    Query or change the count-changes flag. Normally, when the count-changes flag is not set, INSERT, UPDATE and DELETE statements return no data. When count-changes is set, each of these commands returns a single row of data consisting of one integer value - the number of rows inserted, modified or deleted by the command. The returned change count does not include any insertions, modifications or deletions performed by triggers.

  • PRAGMA default_cache_size;
    PRAGMA default_cache_size =
    Number-of-pages;

    Query or change the maximum number of database disk pages that SQLite will hold in memory at once. Each page uses 1K on disk and about 1.5K in memory. This pragma works like the cache_size pragma with the additional feature that it changes the cache size persistently. With this pragma, you can set the cache size once and that setting is retained and reused every time you reopen the database.

  • PRAGMA default_synchronous;

    This pragma was available in version 2.8 but was removed in version 3.0. It is a dangerous pragma whose use is discouraged. To help dissuide users of version 2.8 from employing this pragma, the documentation will not tell you what it does.

  • PRAGMA empty_result_callbacks;
    PRAGMA empty_result_callbacks =
    0 | 1;

    Query or change the empty-result-callbacks flag.

    The empty-result-callbacks flag affects the sqlite3_exec API only. Normally, when the empty-result-callbacks flag is cleared, the callback function supplied to the sqlite3_exec() call is not invoked for commands that return zero rows of data. When empty-result-callbacks is set in this situation, the callback function is invoked exactly once, with the third parameter set to 0 (NULL). This is to enable programs that use the sqlite3_exec() API to retrieve column-names even when a query returns no data.

  • PRAGMA encoding;
    PRAGMA encoding = "UTF-8";
    PRAGMA encoding = "UTF-16";
    PRAGMA encoding = "UTF-16le";
    PRAGMA encoding = "UTF-16be";

    In first form, if the main database has already been created, then this pragma returns the text encoding used by the main database, one of "UTF-8", "UTF-16le" (little-endian UTF-16 encoding) or "UTF-16be" (big-endian UTF-16 encoding). If the main database has not already been created, then the value returned is the text encoding that will be used to create the main database, if it is created by this session.

    The second and subsequent forms of this pragma are only useful if the main database has not already been created. In this case the pragma sets the encoding that the main database will be created with if it is created by this session. The string "UTF-16" is interpreted as "UTF-16 encoding using native machine byte-ordering". If the second and subsequent forms are used after the database file has already been created, they have no effect and are silently ignored.

    Once an encoding has been set for a database, it cannot be changed.

    Databases created by the ATTACH command always use the same encoding as the main database.

  • PRAGMA full_column_names;
    PRAGMA full_column_names =
    0 | 1;

    Query or change the full-column-names flag. This flag affects the way SQLite names columns of data returned by SELECT statements when the expression for the column is a table-column name or the wildcard "*". Normally, such result columns are named <table-name/alias><column-name> if the SELECT statement joins two or more tables together, or simply <column-name> if the SELECT statement queries a single table. When the full-column-names flag is set, such columns are always named <table-name/alias> <column-name> regardless of whether or not a join is performed.

    If both the short-column-names and full-column-names are set, then the behaviour associated with the full-column-names flag is exhibited.

  • PRAGMA fullfsync
    PRAGMA fullfsync =
    0 | 1;

    Query or change the fullfsync flag. This flag affects determines whether or not the F_FULLFSYNC syncing method is used on systems that support it. The default value is off. As of this writing (2006-02-10) only Mac OS X supports F_FULLFSYNC.

  • PRAGMA page_size;
    PRAGMA page_size =
    bytes;

    Query or set the page-size of the database. The page-size may only be set if the database has not yet been created. The page size must be a power of two greater than or equal to 512 and less than or equal to 8192. The upper limit may be modified by setting the value of macro SQLITE_MAX_PAGE_SIZE during compilation. The maximum upper bound is 32768.

  • PRAGMA read_uncommitted;
    PRAGMA read_uncommitted =
    0 | 1;

    Query, set, or clear READ UNCOMMITTED isolation. The default isolation level for SQLite is SERIALIZABLE. Any process or thread can select READ UNCOMMITTED isolation, but SERIALIZABLE will still be used except between connections that share a common page and schema cache. Cache sharing is enabled using the sqlite3_enable_shared_cache() API and is only available between connections running the same thread. Cache sharing is off by default.

  • PRAGMA short_column_names;
    PRAGMA short_column_names =
    0 | 1;

    Query or change the short-column-names flag. This flag affects the way SQLite names columns of data returned by SELECT statements when the expression for the column is a table-column name or the wildcard "*". Normally, such result columns are named <table-name/alias>lt;column-name> if the SELECT statement joins two or more tables together, or simply <column-name> if the SELECT statement queries a single table. When the short-column-names flag is set, such columns are always named <column-name> regardless of whether or not a join is performed.

    If both the short-column-names and full-column-names are set, then the behaviour associated with the full-column-names flag is exhibited.

  • PRAGMA synchronous;
    PRAGMA synchronous = FULL;
    (2)
    PRAGMA synchronous = NORMAL;
    (1)
    PRAGMA synchronous = OFF;
    (0)

    Query or change the setting of the "synchronous" flag. The first (query) form will return the setting as an integer. When synchronous is FULL (2), the SQLite database engine will pause at critical moments to make sure that data has actually been written to the disk surface before continuing. This ensures that if the operating system crashes or if there is a power failure, the database will be uncorrupted after rebooting. FULL synchronous is very safe, but it is also slow. When synchronous is NORMAL, the SQLite database engine will still pause at the most critical moments, but less often than in FULL mode. There is a very small (though non-zero) chance that a power failure at just the wrong time could corrupt the database in NORMAL mode. But in practice, you are more likely to suffer a catastrophic disk failure or some other unrecoverable hardware fault. With synchronous OFF (0), SQLite continues without pausing as soon as it has handed data off to the operating system. If the application running SQLite crashes, the data will be safe, but the database might become corrupted if the operating system crashes or the computer loses power before that data has been written to the disk surface. On the other hand, some operations are as much as 50 or more times faster with synchronous OFF.

    In SQLite version 2, the default value is NORMAL. For version 3, the default was changed to FULL.

  • PRAGMA temp_store;
    PRAGMA temp_store = DEFAULT;
    (0)
    PRAGMA temp_store = FILE;
    (1)
    PRAGMA temp_store = MEMORY;
    (2)

    Query or change the setting of the "temp_store" parameter. When temp_store is DEFAULT (0), the compile-time C preprocessor macro TEMP_STORE is used to determine where temporary tables and indices are stored. When temp_store is MEMORY (2) temporary tables and indices are kept in memory. When temp_store is FILE (1) temporary tables and indices are stored in a file. The temp_store_directory pragma can be used to specify the directory containing this file. FILE is specified. When the temp_store setting is changed, all existing temporary tables, indices, triggers, and views are immediately deleted.

    It is possible for the library compile-time C preprocessor symbol TEMP_STORE to override this pragma setting. The following table summarizes the interaction of the TEMP_STORE preprocessor macro and the temp_store pragma:

    TEMP_STORE PRAGMA
    temp_store
    Storage used for
    TEMP tables and indices
    0 any file
    1 0 file
    1 1 file
    1 2 memory
    2 0 memory
    2 1 file
    2 2 memory
    3 any memory

  • PRAGMA temp_store_directory;
    PRAGMA temp_store_directory = 'directory-name';

    Query or change the setting of the "temp_store_directory" - the directory where files used for storing temporary tables and indices are kept. This setting lasts for the duration of the current connection only and resets to its default value for each new connection opened.

    When the temp_store_directory setting is changed, all existing temporary tables, indices, triggers, and viewers are immediately deleted. In practice, temp_store_directory should be set immediately after the database is opened.

    The value directory-name should be enclosed in single quotes. To revert the directory to the default, set the directory-name to an empty string, e.g., PRAGMA temp_store_directory = ''. An error is raised if directory-name is not found or is not writable.

    The default directory for temporary files depends on the OS. For Unix/Linux/OSX, the default is the is the first writable directory found in the list of: /var/tmp, /usr/tmp, /tmp, and current-directory. For Windows NT, the default directory is determined by Windows, generally C:\Documents and Settings\user-name\Local Settings\Temp\. Temporary files created by SQLite are unlinked immediately after opening, so that the operating system can automatically delete the files when the SQLite process exits. Thus, temporary files are not normally visible through ls or dir commands.


Pragmas to query the database schema

  • PRAGMA database_list;

    For each open database, invoke the callback function once with information about that database. Arguments include the index and the name the database was attached with. The first row will be for the main database. The second row will be for the database used to store temporary tables.

  • PRAGMA foreign_key_list(table-name);

    For each foreign key that references a column in the argument table, invoke the callback function with information about that foreign key. The callback function will be invoked once for each column in each foreign key.

  • PRAGMA index_info(index-name);

    For each column that the named index references, invoke the callback function once with information about that column, including the column name, and the column number.

  • PRAGMA index_list(table-name);

    For each index on the named table, invoke the callback function once with information about that index. Arguments include the index name and a flag to indicate whether or not the index must be unique.

  • PRAGMA table_info(table-name);

    For each column in the named table, invoke the callback function once with information about that column, including the column name, data type, whether or not the column can be NULL, and the default value for the column.


Pragmas to query/modify version values

  • PRAGMA [database.]schema_version;
    PRAGMA [database.]schema_version =
    integer ;
    PRAGMA [database.]user_version;
    PRAGMA [database.]user_version =
    integer ;

    The pragmas schema_version and user_version are used to set or get the value of the schema-version and user-version, respectively. Both the schema-version and the user-version are 32-bit signed integers stored in the database header.

    The schema-version is usually only manipulated internally by SQLite. It is incremented by SQLite whenever the database schema is modified (by creating or dropping a table or index). The schema version is used by SQLite each time a query is executed to ensure that the internal cache of the schema used when compiling the SQL query matches the schema of the database against which the compiled query is actually executed. Subverting this mechanism by using "PRAGMA schema_version" to modify the schema-version is potentially dangerous and may lead to program crashes or database corruption. Use with caution!

    The user-version is not used internally by SQLite. It may be used by applications for any purpose.


Pragmas to debug the library

  • PRAGMA integrity_check;

    The command does an integrity check of the entire database. It looks for out-of-order records, missing pages, malformed records, and corrupt indices. If any problems are found, then a single string is returned which is a description of all problems. If everything is in order, "ok" is returned.

  • PRAGMA parser_trace = ON; (1)
    PRAGMA parser_trace = OFF;
    (0)

    Turn tracing of the SQL parser inside of the SQLite library on and off. This is used for debugging. This only works if the library is compiled without the NDEBUG macro.

  • PRAGMA vdbe_trace = ON; (1)
    PRAGMA vdbe_trace = OFF;
    (0)

    Turn tracing of the virtual database engine inside of the SQLite library on and off. This is used for debugging. See the VDBE documentation for more information.

  • PRAGMA vdbe_listing = ON; (1)
    PRAGMA vdbe_listing = OFF;
    (0)

    Turn listings of virtual machine programs on and off. With listing is on, the entire content of a program is printed just prior to beginning execution. This is like automatically executing an EXPLAIN prior to each statement. The statement executes normally after the listing is printed. This is used for debugging. See the VDBE documentation for more information.


SQLite keywords

The following keywords are used by SQLite. Most are either reserved words in SQL-92 or were listed as potential reserved words. Those which aren't are shown in italics. Not all of these words are actually used by SQLite. Keywords are not reserved in SQLite. Any keyword can be used as an identifier for SQLite objects (columns, databases, indexes, tables, triggers, views, ...) but must generally be enclosed by brackets or quotes to avoid confusing the parser. Keyword matching in SQLite is case-insensitive.

Keywords can be used as identifiers in three ways:

'keyword' Interpreted as a literal string if it occurs in a legal string context, otherwise as an identifier.
"keyword" Interpreted as an identifier if it matches a known identifier and occurs in a legal identifier context, otherwise as a string.
[keyword] Always interpreted as an identifer. (This notation is used by MS Access and SQL Server.)

Fallback Keywords

These keywords can be used as identifiers for SQLite objects without delimiters.

ABORT    AFTER    ASC    ATTACH    BEFORE    BEGIN    DEFERRED    CASCADE    CLUSTER    CONFLICT    COPY    CROSS    DATABASE    DELIMITERS    DESC    DETACH    EACH    END    EXPLAIN    FAIL    FOR    FULL    IGNORE    IMMEDIATE    INITIALLY    INNER    INSTEAD    KEY    LEFT    MATCH    NATURAL    OF    OFFSET    OUTER    PRAGMA    RAISE    REPLACE    RESTRICT    RIGHT    ROW    STATEMENT    TEMP    TEMPORARY    TRIGGER    VACUUM    VIEW   

Normal keywords

These keywords can be used as identifiers for SQLite objects, but must be enclosed in brackets or quotes for SQLite to recognize them as an identifier.

ALL    AND    AS    BETWEEN    BY    CASE    CHECK    COLLATE    COMMIT    CONSTRAINT    CREATE    DEFAULT    DEFERRABLE    DELETE    DISTINCT    DROP    ELSE    EXCEPT    FOREIGN    FROM    GLOB    GROUP    HAVING    IN    INDEX    INSERT    INTERSECT    INTO    IS    ISNULL    JOIN    LIKE    LIMIT    NOT    NOTNULL    NULL    ON    OR    ORDER    PRIMARY    REFERENCES    ROLLBACK    SELECT    SET    TABLE    THEN    TRANSACTION    UNION    UNIQUE    UPDATE    USING    VALUES    WHEN    WHERE   

Special words

The following are not keywords in SQLite, but are used as names of system objects. They can be used as an identifier for a different type of object.

_ROWID_    MAIN    OID    ROWID    SQLITE_MASTER    SQLITE_TEMP_MASTER   


Datatypes In SQLite Version 3

1. Storage Classes

Version 2 of SQLite stores all column values as ASCII text. Version 3 enhances this by providing the ability to store integer and real numbers in a more compact format and the capability to store BLOB data.

Each value stored in an SQLite database (or manipulated by the database engine) has one of the following storage classes:

  • NULL. The value is a NULL value.

  • INTEGER. The value is a signed integer, stored in 1, 2, 3, 4, 6, or 8 bytes depending on the magnitude of the value.

  • REAL. The value is a floating point value, stored as an 8-byte IEEE floating point number.

  • TEXT. The value is a text string, stored using the database encoding (UTF-8, UTF-16BE or UTF-16-LE).

  • BLOB. The value is a blob of data, stored exactly as it was input.

As in SQLite version 2, any column in a version 3 database except an INTEGER PRIMARY KEY may be used to store any type of value. The exception to this rule is described below under 'Strict Affinity Mode'.

All values supplied to SQLite, whether as literals embedded in SQL statements or values bound to pre-compiled SQL statements are assigned a storage class before the SQL statement is executed. Under circumstances described below, the database engine may convert values between numeric storage classes (INTEGER and REAL) and TEXT during query execution.

Storage classes are initially assigned as follows:

  • Values specified as literals as part of SQL statements are assigned storage class TEXT if they are enclosed by single or double quotes, INTEGER if the literal is specified as an unquoted number with no decimal point or exponent, REAL if the literal is an unquoted number with a decimal point or exponent and NULL if the value is a NULL. Literals with storage class BLOB are specified using the X'ABCD' notation.

  • Values supplied using the sqlite3_bind_* APIs are assigned the storage class that most closely matches the native type bound (i.e. sqlite3_bind_blob() binds a value with storage class BLOB).

The storage class of a value that is the result of an SQL scalar operator depends on the outermost operator of the expression. User-defined functions may return values with any storage class. It is not generally possible to determine the storage class of the result of an expression at compile time.

2. Column Affinity

In SQLite version 3, the type of a value is associated with the value itself, not with the column or variable in which the value is stored. (This is sometimes called manifest typing.) All other SQL databases engines that we are aware of use the more restrictive system of static typing where the type is associated with the container, not the value.

In order to maximize compatibility between SQLite and other database engines, SQLite support the concept of "type affinity" on columns. The type affinity of a column is the recommended type for data stored in that column. The key here is that the type is recommended, not required. Any column can still store any type of data, in theory. It is just that some columns, given the choice, will prefer to use one storage class over another. The preferred storage class for a column is called its "affinity".

Each column in an SQLite 3 database is assigned one of the following type affinities:

  • TEXT
  • NUMERIC
  • INTEGER
  • REAL
  • NONE

A column with TEXT affinity stores all data using storage classes NULL, TEXT or BLOB. If numerical data is inserted into a column with TEXT affinity it is converted to text form before being stored.

A column with NUMERIC affinity may contain values using all five storage classes. When text data is inserted into a NUMERIC column, an attempt is made to convert it to an integer or real number before it is stored. If the conversion is successful, then the value is stored using the INTEGER or REAL storage class. If the conversion cannot be performed the value is stored using the TEXT storage class. No attempt is made to convert NULL or blob values.

A column that uses INTEGER affinity behaves in the same way as a column with NUMERIC affinity, except that if a real value with no floating point component (or text value that converts to such) is inserted it is converted to an integer and stored using the INTEGER storage class.

A column with REAL affinity behaves like a column with NUMERIC affinity except that it forces integer values into floating point representation. (As an optimization, integer values are stored on disk as integers in order to take up less space and are only converted to floating point as the value is read out of the table.)

A column with affinity NONE does not prefer one storage class over another. It makes no attempt to coerce data before it is inserted.

2.1 Determination Of Column Affinity

The type affinity of a column is determined by the declared type of the column, according to the following rules:

  1. If the datatype contains the string "INT" then it is assigned INTEGER affinity.

  2. If the datatype of the column contains any of the strings "CHAR", "CLOB", or "TEXT" then that column has TEXT affinity. Notice that the type VARCHAR contains the string "CHAR" and is thus assigned TEXT affinity.

  3. If the datatype for a column contains the string "BLOB" or if no datatype is specified then the column has affinity NONE.

  4. If the datatype for a column contains any of the strings "REAL", "FLOA", or "DOUB" then the column has REAL affinity

  5. Otherwise, the affinity is NUMERIC.

If a table is created using a "CREATE TABLE <table> AS SELECT..." statement, then all columns have no datatype specified and they are given no affinity.

2.2 Column Affinity Example

CREATE TABLE t1(
    t  TEXT,
    nu NUMERIC, 
    i  INTEGER,
    no BLOB
);

-- Storage classes for the following row:
-- TEXT, REAL, INTEGER, TEXT
INSERT INTO t1 VALUES('500.0', '500.0', '500.0', '500.0');

-- Storage classes for the following row:
-- TEXT, REAL, INTEGER, REAL
INSERT INTO t1 VALUES(500.0, 500.0, 500.0, 500.0);

3. Comparison Expressions

Like SQLite version 2, version 3 features the binary comparison operators '=', '<', '<=', '>=' and '!=', an operation to test for set membership, 'IN', and the ternary comparison operator 'BETWEEN'.

The results of a comparison depend on the storage classes of the two values being compared, according to the following rules:

  • A value with storage class NULL is considered less than any other value (including another value with storage class NULL).

  • An INTEGER or REAL value is less than any TEXT or BLOB value. When an INTEGER or REAL is compared to another INTEGER or REAL, a numerical comparison is performed.

  • A TEXT value is less than a BLOB value. When two TEXT values are compared, the C library function memcmp() is usually used to determine the result. However this can be overridden, as described under 'User-defined collation Sequences' below.

  • When two BLOB values are compared, the result is always determined using memcmp().

SQLite may attempt to convert values between the numeric storage classes (INTEGER and REAL) and TEXT before performing a comparison. For binary comparisons, this is done in the cases enumerated below. The term "expression" used in the bullet points below means any SQL scalar expression or literal other than a column value.

  • When a column value is compared to the result of an expression, the affinity of the column is applied to the result of the expression before the comparison takes place.

  • When two column values are compared, if one column has INTEGER or NUMERIC affinity and the other does not, the NUMERIC affinity is applied to any values with storage class TEXT extracted from the non-NUMERIC column.

  • When the results of two expressions are compared, no conversions occur. The results are compared as is. If a string is compared to a number, the number will always be less than the string.

In SQLite, the expression "a BETWEEN b AND c" is equivalent to "a >= b AND a <= c", even if this means that different affinities are applied to 'a' in each of the comparisons required to evaluate the expression.

Expressions of the type "a IN (SELECT b ....)" are handled by the three rules enumerated above for binary comparisons (e.g. in a similar manner to "a = b"). For example if 'b' is a column value and 'a' is an expression, then the affinity of 'b' is applied to 'a' before any comparisons take place.

SQLite treats the expression "a IN (x, y, z)" as equivalent to "a = z OR a = y OR a = z".

3.1 Comparison Example

CREATE TABLE t1(
    a TEXT,
    b NUMERIC,
    c BLOB
);

-- Storage classes for the following row:
-- TEXT, REAL, TEXT
INSERT INTO t1 VALUES('500', '500', '500');

-- 60 and 40 are converted to '60' and '40' and values are compared as TEXT.
SELECT a < 60, a < 40 FROM t1;
1|0

-- Comparisons are numeric. No conversions are required.
SELECT b < 60, b < 600 FROM t1;
0|1

-- Both 60 and 600 (storage class NUMERIC) are less than '500'
-- (storage class TEXT).
SELECT c < 60, c < 600 FROM t1;
0|0

4. Operators

All mathematical operators (which is to say, all operators other than the concatenation operator "||") apply NUMERIC affinity to all operands prior to being carried out. If one or both operands cannot be converted to NUMERIC then the result of the operation is NULL.

For the concatenation operator, TEXT affinity is applied to both operands. If either operand cannot be converted to TEXT (because it is NULL or a BLOB) then the result of the concatenation is NULL.

5. Sorting, Grouping and Compound SELECTs

When values are sorted by an ORDER by clause, values with storage class NULL come first, followed by INTEGER and REAL values interspersed in numeric order, followed by TEXT values usually in memcmp() order, and finally BLOB values in memcmp() order. No storage class conversions occur before the sort.

When grouping values with the GROUP BY clause values with different storage classes are considered distinct, except for INTEGER and REAL values which are considered equal if they are numerically equal. No affinities are applied to any values as the result of a GROUP by clause.

The compound SELECT operators UNION, INTERSECT and EXCEPT perform implicit comparisons between values. Before these comparisons are performed an affinity may be applied to each value. The same affinity, if any, is applied to all values that may be returned in a single column of the compound SELECT result set. The affinity applied is the affinity of the column returned by the left most component SELECTs that has a column value (and not some other kind of expression) in that position. If for a given compound SELECT column none of the component SELECTs return a column value, no affinity is applied to the values from that column before they are compared.

6. Other Affinity Modes

The above sections describe the operation of the database engine in 'normal' affinity mode. SQLite version 3 will feature two other affinity modes, as follows:

  • Strict affinity mode. In this mode if a conversion between storage classes is ever required, the database engine returns an error and the current statement is rolled back.

  • No affinity mode. In this mode no conversions between storage classes are ever performed. Comparisons between values of different storage classes (except for INTEGER and REAL) are always false.

7. User-defined Collation Sequences

By default, when SQLite compares two text values, the result of the comparison is determined using memcmp(), regardless of the encoding of the string. SQLite v3 provides the ability for users to supply arbitrary comparison functions, known as user-defined collation sequences, to be used instead of memcmp().

Aside from the default collation sequence BINARY, implemented using memcmp(), SQLite features one extra built-in collation sequences intended for testing purposes, the NOCASE collation:

  • BINARY - Compares string data using memcmp(), regardless of text encoding.
  • NOCASE - The same as binary, except the 26 upper case characters used by the English language are folded to their lower case equivalents before the comparison is performed.

7.1 Assigning Collation Sequences from SQL

Each column of each table has a default collation type. If a collation type other than BINARY is required, a COLLATE clause is specified as part of the column definition to define it.

Whenever two text values are compared by SQLite, a collation sequence is used to determine the results of the comparison according to the following rules. Sections 3 and 5 of this document describe the circumstances under which such a comparison takes place.

For binary comparison operators (=, <, >, <= and >=) if either operand is a column, then the default collation type of the column determines the collation sequence to use for the comparison. If both operands are columns, then the collation type for the left operand determines the collation sequence used. If neither operand is a column, then the BINARY collation sequence is used.

The expression "x BETWEEN y and z" is equivalent to "x >= y AND x <= z". The expression "x IN (SELECT y ...)" is handled in the same way as the expression "x = y" for the purposes of determining the collation sequence to use. The collation sequence used for expressions of the form "x IN (y, z ...)" is the default collation type of x if x is a column, or BINARY otherwise.

An ORDER BY clause that is part of a SELECT statement may be assigned a collation sequence to be used for the sort operation explicitly. In this case the explicit collation sequence is always used. Otherwise, if the expression sorted by an ORDER BY clause is a column, then the default collation type of the column is used to determine sort order. If the expression is not a column, then the BINARY collation sequence is used.

7.2 Collation Sequences Example

The examples below identify the collation sequences that would be used to determine the results of text comparisons that may be performed by various SQL statements. Note that a text comparison may not be required, and no collation sequence used, in the case of numeric, blob or NULL values.

CREATE TABLE t1(
    a,                 -- default collation type BINARY
    b COLLATE BINARY,  -- default collation type BINARY
    c COLLATE REVERSE, -- default collation type REVERSE
    d COLLATE NOCASE   -- default collation type NOCASE
);

-- Text comparison is performed using the BINARY collation sequence.
SELECT (a = b) FROM t1;

-- Text comparison is performed using the NOCASE collation sequence.
SELECT (d = a) FROM t1;

-- Text comparison is performed using the BINARY collation sequence.
SELECT (a = d) FROM t1;

-- Text comparison is performed using the REVERSE collation sequence.
SELECT ('abc' = c) FROM t1;

-- Text comparison is performed using the REVERSE collation sequence.
SELECT (c = 'abc') FROM t1;

-- Grouping is performed using the NOCASE collation sequence (i.e. values
-- 'abc' and 'ABC' are placed in the same group).
SELECT count(*) GROUP BY d FROM t1;

-- Grouping is performed using the BINARY collation sequence.
SELECT count(*) GROUP BY (d || '') FROM t1;

-- Sorting is performed using the REVERSE collation sequence.
SELECT * FROM t1 ORDER BY c;

-- Sorting is performed using the BINARY collation sequence.
SELECT * FROM t1 ORDER BY (c || '');

-- Sorting is performed using the NOCASE collation sequence.
SELECT * FROM t1 ORDER BY c COLLATE NOCASE;


Distinctive Features Of SQLite

This page highlights some of the characteristics of SQLite that are unusual and which make SQLite different from many other SQL database engines.

Zero-Configuration

SQLite does not need to be "installed" before it is used. There is no "setup" procedure. There is no server process that needs to be started, stopped, or configured. There is no need for an administrator to create a new database instance or assign access permissions to users. SQLite uses no configuration files. Nothing needs to be done to tell the system that SQLite is running. No actions are required to recover after a system crash or power failure. There is nothing to troubleshoot.

SQLite just works.

Other more familiar database engines run great once you get them going. But doing the initial installation and configuration can be intimidatingly complex.

Serverless

Most SQL database engines are implemented as a separate server process. Programs that want to access the database communicate with the server using some kind of interprocess communcation (typically TCP/IP) to send requests to the server and to receive back results. SQLite does not work this way. With SQLite, the process that wants to access the database reads and writes directly from the database files on disk. There is no intermediary server process.

There are advantages and disadvantages to being serverless. The main advantage is that there is no separate server process to install, setup, configure, initialize, manage, and troubleshoot. This is one reason why SQLite is a "zero-configuration" database engine. Programs that use SQLite require no administrative support for setting up the database engine before they are run. Any program that is able to access the disk is able to use an SQLite database.

On the other hand, a database engine that uses a server can provide better protection from bugs in the client application - stray pointers in a client cannot corrupt memory on the server. And because a server is a single persistent process, it is able control database access with more precision, allowing for finer grain locking and better concurrancy.

Most SQL database engines are client/server based. Of those that are serverless, SQLite is the only one that this author knows of that allows multiple applications to access the same database at the same time.

Single Database File

An SQLite database is a single ordinary disk file that can be located anywhere in the directory hierarchy. If SQLite can read the disk file then it can read anything in the database. If the disk file and its directory are writable, then SQLite can change anything in the database. Database files can easily be copied onto a USB memory stick or emailed for sharing.

Other SQL database engines tend to store data as a large collection of files. Often these files are in a standard location that only the database engine itself can access. This makes the data more secure, but also makes it harder to access. Some SQL database engines provide the option of writing directly to disk and bypassing the filesystem all together. This provides added performance, but at the cost of considerable setup and maintenance complexity.

Compact

When optimized for size, the whole SQLite library with everything enabled is less than 225KiB in size (as measured on an ix86 using the "size" utility from the GNU compiler suite.) Unneeded features can be disabled at compile-time to further reduce the size of the library to under 170KiB if desired.

Most other SQL database engines are much larger than this. IBM boasts that it's recently released CloudScape database engine is "only" a 2MiB jar file - 10 times larger than SQLite even after it is compressed! Firebird boasts that it's client-side library is only 350KiB. That's 50% larger than SQLite and does not even contain the database engine. The Berkeley DB library from Sleepycat is 450KiB and it omits SQL support, providing the programmer with only simple key/value pairs.

Manifest typing

Most SQL database engines use static typing. A datatype is associated with each column in a table and only values of that particular datatype are allowed to be stored in that column. SQLite relaxes this restriction by using manifest typing. In manifest typing, the datatype is a property of the value itself, not of the column in which the value is stored. SQLite thus allows the user to store any value of any datatype into any column regardless of the declared type of that column. (There are some exceptions to this rule: An INTEGER PRIMARY KEY column may only store integers. And SQLite attempts to coerce values into the declared datatype of the column when it can.)

The SQL language specification calls for static typing. So some people feel that the use of manifest typing is a bug in SQLite. But the authors of SQLite feel very strongly that this is a feature. The authors argue that static typing is a bug in the SQL specification that SQLite has fixed in a backwards compatible way.

Variable-length records

Most other SQL database engines allocated a fixed amount of disk space for each row in most tables. They play special tricks for handling BLOBs and CLOBs which can be of wildly varying length. But for most tables, if you declare a column to be a VARCHAR(100) then the database engine will allocate 100 bytes of disk space regardless of how much information you actually store in that column.

SQLite, in contrast, use only the amount of disk space actually needed to store the information in a row. If you store a single character in a VARCHAR(100) column, then only a single byte of disk space is consumed. (Actually two bytes - there is some overhead at the beginning of each column to record its datatype and length.)

The use of variable-length records by SQLite has a number of advantages. It results in smaller database files, obviously. It also makes the database run faster, since there is less information to move to and from disk. And, the use of variable-length records makes it possible for SQLite to employ manifest typing instead of static typing.

Readable source code

The source code to SQLite is designed to be readable and accessible to the average programmer. All procedures and data structures and many automatic variables are carefully commented with useful information about what they do. Boilerplate commenting is omitted.

SQL statements compile into virtual machine code

Every SQL database engine compiles each SQL statement into some kind of internal data structure which is then used to carry out the work of the statement. But in most SQL engines that internal data structure is a complex web of interlinked structures and objects. In SQLite, the compiled form of statements is a short program in a machine-language like representation. Users of the database can view this virtual machine language by prepending the EXPLAIN keyword to a query.

The use of a virtual machine in SQLite has been a great benefit to library's development. The virtual machine provides a crisp, well-defined junction between the front-end of SQLite (the part that parses SQL statements and generates virtual machine code) and the back-end (the part that executes the virtual machine code and computes a result.) The virtual machine allows the developers to see clearly and in an easily readable form what SQLite is trying to do with each statement it compiles, which is a tremendous help in debugging. Depending on how it is compiled, SQLite also has the capability of tracing the execution of the virtual machine - printing each virtual machine instruction and its result as it executes.

Public domain

The source code for SQLite is in the public domain. No claim of copyright is made on any part of the core source code. (The documentation and test code is a different matter - some sections of documentation and test logic are governed by open-sources licenses.) All contributors to the SQLite core software have signed affidavits specifically disavowing any copyright interest in the code. This means that anybody is able to legally do anything they want with the SQLite source code.

There are other SQL database engines with liberal licenses that allow the code to be broadly and freely used. But those other engines are still governed by copyright law. SQLite is different in that copyright law simply does not apply.

The source code files for other SQL database engines typically begin with a comment describing your license rights to view and copy that file. The SQLite source code contains no license since it is not governed by copyright. Instead of a license, the SQLite source code offers a blessing:

May you do good and not evil
May you find forgiveness for yourself and forgive others
May you share freely, never taking more than you give.

SQL language extensions

SQLite provides a number of enhancements to the SQL language not normally found in other database engines. The EXPLAIN keyword and manifest typing have already been mentioned above. SQLite also provides statements such as REPLACE and the ON CONFLICT clause that allow for added control over the resolution of constraint conflicts. SQLite supports ATTACH and DETACH commands that allow multiple independent databases to be used together in the same query. And SQLite defines APIs that allows the user to add new SQL functions and collating sequences.

NULL Handling in SQLite Versus Other Database Engines

The goal is to make SQLite handle NULLs in a standards-compliant way. But the descriptions in the SQL standards on how to handle NULLs seem ambiguous. It is not clear from the standards documents exactly how NULLs should be handled in all circumstances.

So instead of going by the standards documents, various popular SQL engines were tested to see how they handle NULLs. The idea was to make SQLite work like all the other engines. A SQL test script was developed and run by volunteers on various SQL RDBMSes and the results of those tests were used to deduce how each engine processed NULL values. The original tests were run in May of 2002. A copy of the test script is found at the end of this document.

SQLite was originally coded in such a way that the answer to all questions in the chart below would be "Yes". But the experiments run on other SQL engines showed that none of them worked this way. So SQLite was modified to work the same as Oracle, PostgreSQL, and DB2. This involved making NULLs indistinct for the purposes of the SELECT DISTINCT statement and for the UNION operator in a SELECT. NULLs are still distinct in a UNIQUE column. This seems somewhat arbitrary, but the desire to be compatible with other engines outweighted that objection.

It is possible to make SQLite treat NULLs as distinct for the purposes of the SELECT DISTINCT and UNION. To do so, one should change the value of the NULL_ALWAYS_DISTINCT #define in the sqliteInt.h source file and recompile.

Update 2003-07-13: Since this document was originally written some of the database engines tested have been updated and users have been kind enough to send in corrections to the chart below. The original data showed a wide variety of behaviors, but over time the range of behaviors has converged toward the PostgreSQL/Oracle model. The only significant difference is that Informix and MS-SQL both threat NULLs as indistinct in a UNIQUE column.

The fact that NULLs are distinct for UNIQUE columns but are indistinct for SELECT DISTINCT and UNION continues to be puzzling. It seems that NULLs should be either distinct everywhere or nowhere. And the SQL standards documents suggest that NULLs should be distinct everywhere. Yet as of this writing, no SQL engine tested treats NULLs as distinct in a SELECT DISTINCT statement or in a UNION.

The following table shows the results of the NULL handling experiments.

   SQLite PostgreSQL Oracle Informix DB2 MS-SQL OCELOT
Adding anything to null gives null Yes Yes Yes Yes Yes Yes Yes
Multiplying null by zero gives null Yes Yes Yes Yes Yes Yes Yes
nulls are distinct in a UNIQUE column Yes Yes Yes No (Note 4) No Yes
nulls are distinct in SELECT DISTINCT No No No No No No No
nulls are distinct in a UNION No No No No No No No
"CASE WHEN null THEN 1 ELSE 0 END" is 0? Yes Yes Yes Yes Yes Yes Yes
"null OR true" is true Yes Yes Yes Yes Yes Yes Yes
"not (null AND false)" is true Yes Yes Yes Yes Yes Yes Yes
   MySQL
3.23.41
MySQL
4.0.16
Firebird SQL
Anywhere
Borland
Interbase
Adding anything to null gives null Yes Yes Yes Yes Yes
Multiplying null by zero gives null Yes Yes Yes Yes Yes
nulls are distinct in a UNIQUE column Yes Yes Yes (Note 4) (Note 4)
nulls are distinct in SELECT DISTINCT No No No (Note 1) No No
nulls are distinct in a UNION (Note 3) No No (Note 1) No No
"CASE WHEN null THEN 1 ELSE 0 END" is 0? Yes Yes Yes Yes (Note 5)
"null OR true" is true Yes Yes Yes Yes Yes
"not (null AND false)" is true No Yes Yes Yes Yes
Notes:   1.  Older versions of firebird omits all NULLs from SELECT DISTINCT and from UNION.
2.  Test data unavailable.
3.  MySQL version 3.23.41 does not support UNION.
4.  DB2, SQL Anywhere, and Borland Interbase do not allow NULLs in a UNIQUE column.
5.  Borland Interbase does not support CASE expressions.

 

The following script was used to gather information for the table above.

-- I have about decided that SQL's treatment of NULLs is capricious and cannot be
-- deduced by logic.  It must be discovered by experiment.  To that end, I have 
-- prepared the following script to test how various SQL databases deal with NULL.
-- My aim is to use the information gather from this script to make SQLite as much
-- like other databases as possible.
--
-- If you could please run this script in your database engine and mail the results
-- to me at drh@hwaci.com, that will be a big help.  Please be sure to identify the
-- database engine you use for this test.  Thanks.
--
-- If you have to change anything to get this script to run with your database
-- engine, please send your revised script together with your results.
--

-- Create a test table with data
create table t1(a int, b int, c int);
insert into t1 values(1,0,0);
insert into t1 values(2,0,1);
insert into t1 values(3,1,0);
insert into t1 values(4,1,1);
insert into t1 values(5,null,0);
insert into t1 values(6,null,1);
insert into t1 values(7,null,null);

-- Check to see what CASE does with NULLs in its test expressions
select a, case when b<>0 then 1 else 0 end from t1;
select a+10, case when not b<>0 then 1 else 0 end from t1;
select a+20, case when b<>0 and c<>0 then 1 else 0 end from t1;
select a+30, case when not (b<>0 and c<>0) then 1 else 0 end from t1;
select a+40, case when b<>0 or c<>0 then 1 else 0 end from t1;
select a+50, case when not (b<>0 or c<>0) then 1 else 0 end from t1;
select a+60, case b when c then 1 else 0 end from t1;
select a+70, case c when b then 1 else 0 end from t1;

-- What happens when you multiple a NULL by zero?
select a+80, b*0 from t1;
select a+90, b*c from t1;

-- What happens to NULL for other operators?
select a+100, b+c from t1;

-- Test the treatment of aggregate operators
select count(*), count(b), sum(b), avg(b), min(b), max(b) from t1;

-- Check the behavior of NULLs in WHERE clauses
select a+110 from t1 where b<10;
select a+120 from t1 where not b>10;
select a+130 from t1 where b<10 OR c=1;
select a+140 from t1 where b<10 AND c=1;
select a+150 from t1 where not (b<10 AND c=1);
select a+160 from t1 where not (c=1 AND b<10);

-- Check the behavior of NULLs in a DISTINCT query
select distinct b from t1;

-- Check the behavior of NULLs in a UNION query
select b from t1 union select b from t1;

-- Create a new table with a unique column.  Check to see if NULLs are considered
-- to be distinct.
create table t2(a int, b int unique);
insert into t2 values(1,1);
insert into t2 values(2,null);
insert into t2 values(3,null);
select * from t2;

drop table t1;
drop table t2;

SQL Features That SQLite Does Not Implement

Rather than try to list all the features of SQL92 that SQLite does support, it is much easier to list those that it does not. Unsupported features of SQL92 are shown below.

The order of this list gives some hint as to when a feature might be added to SQLite. Those features near the top of the list are likely to be added in the near future. There are no immediate plans to add features near the bottom of the list.

FOREIGN KEY constraints   FOREIGN KEY constraints are parsed but are not enforced.
Complete trigger support   There is some support for triggers but it is not complete. Missing subfeatures include FOR EACH STATEMENT triggers (currently all triggers must be FOR EACH ROW), INSTEAD OF triggers on tables (currently INSTEAD OF triggers are only allowed on views), and recursive triggers - triggers that trigger themselves.
Complete ALTER TABLE support   Only the RENAME TABLE and ADD COLUMN variants of the ALTER TABLE command are supported. Other kinds of ALTER TABLE operations such as DROP COLUMN, ALTER COLUMN, ADD CONSTRAINT, and so forth are omitted.
Nested transactions   The current implementation only allows a single active transaction.
RIGHT and FULL OUTER JOIN   LEFT OUTER JOIN is implemented, but not RIGHT OUTER JOIN or FULL OUTER JOIN.
Writing to VIEWs   VIEWs in SQLite are read-only. You may not execute a DELETE, INSERT, or UPDATE statement on a view. But you can create a trigger that fires on an attempt to DELETE, INSERT, or UPDATE a view and do what you need in the body of the trigger.
GRANT and REVOKE   Since SQLite reads and writes an ordinary disk file, the only access permissions that can be applied are the normal file access permissions of the underlying operating system. The GRANT and REVOKE commands commonly found on client/server RDBMSes are not implemented because they would be meaningless for an embedded database engine.

If you find other SQL92 features that SQLite does not support, please add them to the Wiki page at http://www.sqlite.org/cvstrac/wiki?p=UnsupportedSql


SQLite Autoincrement

In SQLite, every row of every table has an integer ROWID. The ROWID for each row is unique among all rows in the same table. In SQLite version 2.8 the ROWID is a 32-bit signed integer. Version 3.0 of SQLite expanded the ROWID to be a 64-bit signed integer.

You can access the ROWID of an SQLite table using one the special column names ROWID, _ROWID_, or OID. Except if you declare an ordinary table column to use one of those special names, then the use of that name will refer to the declared column not to the internal ROWID.

If a table contains a column of type INTEGER PRIMARY KEY, then that column becomes an alias for the ROWID. You can then access the ROWID using any of four different names, the original three names described above or the name given to the INTEGER PRIMARY KEY column. All these names are aliases for one another and work equally well in any context.

When a new row is inserted into an SQLite table, the ROWID can either be specified as part of the INSERT statement or it can be assigned automatically by the database engine. To specify a ROWID manually, just include it in the list of values to be inserted. For example:

CREATE TABLE test1(a INT, b TEXT);
INSERT INTO test1(rowid, a, b) VALUES(123, 5, 'hello');

If no ROWID is specified on the insert, an appropriate ROWID is created automatically. The usual algorithm is to give the newly created row a ROWID that is one larger than the largest ROWID in the table prior to the insert. If the table is initially empty, then a ROWID of 1 is used. If the largest ROWID is equal to the largest possible integer (9223372036854775807 in SQLite version 3.0 and later) then the database engine starts picking candidate ROWIDs at random until it finds one that is not previously used.

The normal ROWID selection algorithm described above will generate monotonically increasing unique ROWIDs as long as you never use the maximum ROWID value and you never delete the entry in the table with the largest ROWID. If you ever delete rows or if you ever create a row with the maximum possible ROWID, then ROWIDs from previously deleted rows might be reused when creating new rows and newly created ROWIDs might not be in strictly accending order.

The AUTOINCREMENT Keyword

If a column has the type INTEGER PRIMARY KEY AUTOINCREMENT then a slightly different ROWID selection algorithm is used. The ROWID chosen for the new row is one larger than the largest ROWID that has ever before existed in that same table. If the table has never before contained any data, then a ROWID of 1 is used. If the table has previously held a row with the largest possible ROWID, then new INSERTs are not allowed and any attempt to insert a new row will fail with an SQLITE_FULL error.

SQLite keeps track of the largest ROWID that a table has ever held using the special SQLITE_SEQUENCE table. The SQLITE_SEQUENCE table is created and initialized automatically whenever a normal table that contains an AUTOINCREMENT column is created. The content of the SQLITE_SEQUENCE table can be modified using ordinary UPDATE, INSERT, and DELETE statements. But making modifications to this table will likely perturb the AUTOINCREMENT key generation algorithm. Make sure you know what you are doing before you undertake such changes.

The behavior implemented by the AUTOINCREMENT keyword is subtly different from the default behavior. With AUTOINCREMENT, rows with automatically selected ROWIDs are guaranteed to have ROWIDs that have never been used before by the same table in the same database. And the automatically generated ROWIDs are guaranteed to be monotonically increasing. These are important properties in certain applications. But if your application does not need these properties, you should probably stay with the default behavior since the use of AUTOINCREMENT requires additional work to be done as each row is inserted and thus causes INSERTs to run a little slower.


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