CREATE_TABLE(7pg13)

📦 version 13.23, in opensuse-leap 16.0

💖 CREATE TABLE 💖

okay so this is CREATE_TABLE(7pg13) from the PostgreSQL 13.23 documentation, and we're doing it in parts bestie — part 1 starts now. No cap, every flag and fact is staying in. 💅

🌸 NAME 🌸

CREATE_TABLE — define a new table. That's the name, that's the vibe, and yes it's giving main character energy. ✨

🦋 SYNOPSIS 🦋

Here's the literal shape of the spell — copy it exactly, no editing, bestie:

CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } | UNLOGGED ] TABLE [ IF NOT EXISTS ] table_name ( [
  { column_name data_type [ COLLATE collation ] [ column_constraint [ ... ] ]
    | table_constraint
    | LIKE source_table [ like_option ... ] }
  [, ... ]
] )
[ INHERITS ( parent_table [, ... ] ) ]
[ PARTITION BY { RANGE | LIST | HASH } ( { column_name | ( expression ) } [ COLLATE collation ] [ opclass ] [, ... ] ) ]
[ USING method ]
[ WITH ( storage_parameter [= value] [, ... ] ) | WITHOUT OIDS ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE tablespace_name ]

CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } | UNLOGGED ] TABLE [ IF NOT EXISTS ] table_name
    OF type_name [ (
  { column_name [ WITH OPTIONS ] [ column_constraint [ ... ] ]
    | table_constraint }
  [, ... ]
) ]
[ PARTITION BY { RANGE | LIST | HASH } ( { column_name | ( expression ) } [ COLLATE collation ] [ opclass ] [, ... ] ) ]
[ USING method ]
[ WITH ( storage_parameter [= value] [, ... ] ) | WITHOUT OIDS ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE tablespace_name ]

CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } | UNLOGGED ] TABLE [ IF NOT EXISTS ] table_name
    PARTITION OF parent_table [ (
  { column_name [ WITH OPTIONS ] [ column_constraint [ ... ] ]
    | table_constraint }
  [, ... ]
) ] { FOR VALUES partition_bound_spec | DEFAULT }
[ PARTITION BY { RANGE | LIST | HASH } ( { column_name | ( expression ) } [ COLLATE collation ] [ opclass ] [, ... ] ) ]
[ USING method ]
[ WITH ( storage_parameter [= value] [, ... ] ) | WITHOUT OIDS ]
[ ON COMMIT { PRESERVE ROWS | DELETE ROWS | DROP } ]
[ TABLESPACE tablespace_name ]

where column_constraint is:

[ CONSTRAINT constraint_name ]
{ NOT NULL |
  NULL |
  CHECK ( expression ) [ NO INHERIT ] |
  DEFAULT default_expr |
  GENERATED ALWAYS AS ( generation_expr ) STORED |
  GENERATED { ALWAYS | BY DEFAULT } AS IDENTITY [ ( sequence_options ) ] |
  UNIQUE index_parameters |
  PRIMARY KEY index_parameters |
  REFERENCES reftable [ ( refcolumn ) ] [ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ]
    [ ON DELETE referential_action ] [ ON UPDATE referential_action ] }
[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

and table_constraint is:

[ CONSTRAINT constraint_name ]
{ CHECK ( expression ) [ NO INHERIT ] |
  UNIQUE ( column_name [, ... ] ) index_parameters |
  PRIMARY KEY ( column_name [, ... ] ) index_parameters |
  EXCLUDE [ USING index_method ] ( exclude_element WITH operator [, ... ] ) index_parameters [ WHERE ( predicate ) ] |
  FOREIGN KEY ( column_name [, ... ] ) REFERENCES reftable [ ( refcolumn [, ... ] ) ]
    [ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ] [ ON DELETE referential_action ] [ ON UPDATE referential_action ] }
[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ]

and like_option is:

{ INCLUDING | EXCLUDING } { COMMENTS | CONSTRAINTS | DEFAULTS | GENERATED | IDENTITY | INDEXES | STATISTICS | STORAGE | ALL }

and partition_bound_spec is:

IN ( partition_bound_expr [, ...] ) |
FROM ( { partition_bound_expr | MINVALUE | MAXVALUE } [, ...] )
  TO ( { partition_bound_expr | MINVALUE | MAXVALUE } [, ...] ) |
WITH ( MODULUS numeric_literal, REMAINDER numeric_literal )

index_parameters in UNIQUE, PRIMARY KEY, and EXCLUDE constraints are:

[ INCLUDE ( column_name [, ... ] ) ]
[ WITH ( storage_parameter [= value] [, ... ] ) ]
[ USING INDEX TABLESPACE tablespace_name ]

exclude_element in an EXCLUDE constraint is:

{ column_name | ( expression ) } [ COLLATE collation ] [ opclass [ ( opclass_parameter = value [, ... ] ) ] ] [ ASC | DESC ] [ NULLS { FIRST | LAST } ]

That's a lot of brackets and I'm obsessed 🎀.

🌈 DESCRIPTION 🌈

okay so CREATE TABLE does exactly what it says on the tin: it creates a new, initially empty table in the current database. The table will be owned by the user issuing the command. Lowkey iconic. ✨

If you give a schema name — for example, CREATE TABLE myschema.mytable ... — then the table is created in the specified schema. Otherwise it is created in the current schema. Temporary tables exist in a special schema, so bestie, a schema name cannot be given when creating a temporary table. The name of the table must be distinct from the name of any other table, sequence, index, view, or foreign table in the same schema. No name collisions, periodt.

CREATE TABLE also automatically creates a data type that represents the composite type corresponding to one row of the table. Therefore, tables cannot have the same name as any existing data type in the same schema. It's giving built-in lore.

The optional constraint clauses specify constraints (tests) that new or updated rows must satisfy for an insert or update operation to succeed. A constraint is an SQL object that helps define the set of valid values in the table in various ways. We love a little structure. 🎀

There are two ways to define constraints: table constraints and column constraints. A column constraint is defined as part of a column definition. A table constraint definition is not tied to a particular column, and it can encompass more than one column. Every column constraint can also be written as a table constraint; a column constraint is only a notational convenience for use when the constraint only affects one column. iykyk.

To be able to create a table, you must have USAGE privilege on all column types or the type in the OF clause, respectively. That's the access vibe check. 💅

🔥 PARAMETERS 🔥

okay bestie, here come the parameters — every single one. Don't skip, fr fr.

  • TEMPORARY or TEMP — If specified, the table is created as a temporary table. Temporary tables are automatically dropped at the end of a session, or optionally at the end of the current transaction (see ON COMMIT below). Existing permanent tables with the same name are not visible to the current session while the temporary table exists, unless they are referenced with schema-qualified names. Any indexes created on a temporary table are automatically temporary as well.
    • The autovacuum daemon cannot access and therefore cannot vacuum or analyze temporary tables. For this reason, appropriate vacuum and analyze operations should be performed via session SQL commands. For example, if a temporary table is going to be used in complex queries, it is wise to run ANALYZE on the temporary table after it is populated.
    • Optionally, GLOBAL or LOCAL can be written before TEMPORARY or TEMP. This presently makes no difference in PostgreSQL and is deprecated; see Compatibility below.
  • UNLOGGED — If specified, the table is created as an unlogged table. Data written to unlogged tables is not written to the write-ahead log (see Chapter 29), which makes them considerably faster than ordinary tables. However, they are not crash-safe: an unlogged table is automatically truncated after a crash or unclean shutdown. The contents of an unlogged table are also not replicated to standby servers. Any indexes created on an unlogged table are automatically unlogged as well.
  • IF NOT EXISTS — Do not throw an error if a relation with the same name already exists. A notice is issued in this case. Note that there is no guarantee that the existing relation is anything like the one that would have been created.
  • table_name — The name (optionally schema-qualified) of the table to be created.
  • OF type_name — Creates a typed table, which takes its structure from the specified composite type (name optionally schema-qualified). A typed table is tied to its type; for example the table will be dropped if the type is dropped (with DROP TYPE ... CASCADE).
    • When a typed table is created, then the data types of the columns are determined by the underlying composite type and are not specified by the CREATE TABLE command. But the CREATE TABLE command can add defaults and constraints to the table and can specify storage parameters.
  • column_name — The name of a column to be created in the new table.
  • data_type — The data type of the column. This can include array specifiers. For more information on the data types supported by PostgreSQL, refer to Chapter 8.
  • COLLATE collation — The COLLATE clause assigns a collation to the column (which must be of a collatable data type). If not specified, the column data type's default collation is used.
  • INHERITS ( parent_table [, ... ] ) — The optional INHERITS clause specifies a list of tables from which the new table automatically inherits all columns. Parent tables can be plain tables or foreign tables.
    • Use of INHERITS creates a persistent relationship between the new child table and its parent table(s). Schema modifications to the parent(s) normally propagate to children as well, and by default the data of the child table is included in scans of the parent(s).
    • If the same column name exists in more than one parent table, an error is reported unless the data types of the columns match in each of the parent tables. If there is no conflict, then the duplicate columns are merged to form a single column in the new table. If the column name list of the new table contains a column name that is also inherited, the data type must likewise match the inherited column(s), and the column definitions are merged into one. If the new table explicitly specifies a default value for the column, this default overrides any defaults from inherited declarations of the column. Otherwise, any parents that specify default values for the column must all specify the same default, or an error will be reported.
    • CHECK constraints are merged in essentially the same way as columns: if multiple parent tables and/or the new table definition contain identically-named CHECK constraints, these constraints must all have the same check expression, or an error will be reported. Constraints having the same name and expression will be merged into one copy. A constraint marked NO INHERIT in a parent will not be considered. Notice that an unnamed CHECK constraint in the new table will never be merged, since a unique name will always be chosen for it.
    • Column STORAGE settings are also copied from parent tables.
    • If a column in the parent table is an identity column, that property is not inherited. A column in the child table can be declared identity column if desired.

and yes, we're still in PARAMETERS — more flags are about to pull up in the next part, bestie 💅

✨ PARTITION BY ✨

PARTITION BY { RANGE | LIST | HASH } ( { column_name | ( expression ) }
[ opclass ] [, ...] )

okay so this optional clause is literally how you tell the table “bestie, you’re gonna be partitioned.” the table you get is called a partitioned table 💅. that parenthesized list of columns or expressions? that’s the partition key for the table, no cap.

when you’re doing range or hash partitioning, the partition key can include multiple columns or expressions — up to 32, but note that this limit can be altered when building PostgreSQL. for list partitioning though? the partition key must be a single column or expression. periodt.

range and list partitioning require a btree operator class, while hash partitioning requires a hash operator class. if you don’t specify an operator class explicitly, the default operator class of the appropriate type gets used; if there’s no default operator class, an error will be raised 😭. when hash partitioning is used, the operator class used must implement support function 2 (see Section 37.16.3 for details).

a partitioned table is divided into sub-tables (called partitions), which are created using separate CREATE TABLE commands. the partitioned table itself is empty — like, literally no rows live there. a data row inserted into the table is routed to a partition based on the value of columns or expressions in the partition key. if no existing partition matches the values in the new row, an error will be reported 💀.

partitioned tables do not support EXCLUDE constraints; however, you can define these constraints on individual partitions. slay for loopholes.

see Section 5.11 for more discussion on table partitioning.

💅 PARTITION OF 💅

PARTITION OF parent_table { FOR VALUES partition_bound_spec | DEFAULT }

this creates the table as a partition of the specified parent table, bestie. the table can be created either as a partition for specific values using FOR VALUES or as a default partition using DEFAULT. any indexes, constraints and user-defined row-level triggers that exist in the parent table are cloned on the new partition — iconic inheritance energy ✨.

the partition_bound_spec must correspond to the partitioning method and partition key of the parent table, and must not overlap with any existing partition of that parent. the form with IN is used for list partitioning, the form with FROM and TO is used for range partitioning, and the form with WITH is used for hash partitioning.

partition_bound_expr is any variable-free expression (subqueries, window functions, aggregate functions, and set-returning functions are not allowed). its data type must match the data type of the corresponding partition key column. the expression is evaluated once at table creation time, so it can even contain volatile expressions such as CURRENT_TIMESTAMP 🫶.

when creating a list partition, NULL can be specified to signify that the partition allows the partition key column to be null. however, there cannot be more than one such list partition for a given parent table. NULL cannot be specified for range partitions.

when creating a range partition, the lower bound specified with FROM is an inclusive bound, whereas the upper bound specified with TO is an exclusive bound. that is, the values specified in the FROM list are valid values of the corresponding partition key columns for this partition, whereas those in the TO list are not. note that this statement must be understood according to the rules of row-wise comparison (Section 9.24.5). for example, given PARTITION BY RANGE (x,y), a partition bound FROM (1, 2) TO (3, 4) allows x=1 with any y>=2, x=2 with any non-null y, and x=3 with any y<4. math is mathing 💖.

the special values MINVALUE and MAXVALUE may be used when creating a range partition to indicate that there is no lower or upper bound on the column’s value. for example, a partition defined using FROM (MINVALUE) TO (10) allows any values less than 10, and a partition defined using FROM (10) TO (MAXVALUE) allows any values greater than or equal to 10.

when creating a range partition involving more than one column, it can also make sense to use MAXVALUE as part of the lower bound, and MINVALUE as part of the upper bound. for example, a partition defined using FROM (0, MAXVALUE) TO (10, MAXVALUE) allows any rows where the first partition key column is greater than 0 and less than or equal to 10. similarly, a partition defined using FROM ('a', MINVALUE) TO ('b', MINVALUE) allows any rows where the first partition key column starts with "a".

note that if MINVALUE or MAXVALUE is used for one column of a partitioning bound, the same value must be used for all subsequent columns. for example, (10, MINVALUE, 0) is not a valid bound; you should write (10, MINVALUE, MINVALUE). don’t try to be cute with it 😭.

also note that some element types, such as timestamp, have a notion of "infinity", which is just another value that can be stored. this is different from MINVALUE and MAXVALUE, which are not real values that can be stored, but rather they are ways of saying that the value is unbounded. MAXVALUE can be thought of as being greater than any other value, including "infinity" and MINVALUE as being less than any other value, including "minus infinity". thus the range FROM ('infinity') TO (MAXVALUE) is not an empty range; it allows precisely one value to be stored — "infinity" 🌈.

if DEFAULT is specified, the table will be created as the default partition of the parent table. this option is not available for hash-partitioned tables. a partition key value not fitting into any other partition of the given parent will be routed to the default partition.

when a table has an existing DEFAULT partition and a new partition is added to it, the default partition must be scanned to verify that it does not contain any rows which properly belong in the new partition. if the default partition contains a large number of rows, this may be slow 🐌. the scan will be skipped if the default partition is a foreign table or if it has a constraint which proves that it cannot contain rows which should be placed in the new partition. thank u, next.

when creating a hash partition, a modulus and remainder must be specified. the modulus must be a positive integer, and the remainder must be a non-negative integer less than the modulus. typically, when initially setting up a hash-partitioned table, you should choose a modulus equal to the number of partitions and assign every table the same modulus and a different remainder (see examples, below). however, it is not required that every partition have the same modulus, only that every modulus which occurs among the partitions of a hash-partitioned table is a factor of the next larger modulus. this allows the number of partitions to be increased incrementally without needing to move all the data at once. for example, suppose you have a hash-partitioned table with 8 partitions, each of which has modulus 8, but find it necessary to increase the number of partitions to 16. you can detach one of the modulus-8 partitions, create two new modulus-16 partitions covering the same portion of the key space (one with a remainder equal to the remainder of the detached partition, and the other with a remainder equal to that value plus 8), and repopulate them with data. you can then repeat this — perhaps at a later time — for each modulus-8 partition until none remain. while this may still involve a large amount of data movement at each step, it is still better than having to create a whole new table and move all the data at once. lowkey genius 🧚.

a partition must have the same column names and types as the partitioned table to which it belongs. modifications to the column names or types of a partitioned table will automatically propagate to all partitions. CHECK constraints will be inherited automatically by every partition, but an individual partition may specify additional CHECK constraints; additional constraints with the same name and condition as in the parent will be merged with the parent constraint. defaults may be specified separately for each partition. but note that a partition’s default value is not applied when inserting a tuple through a partitioned table 🙈.

rows inserted into a partitioned table will be automatically routed to the correct partition. if no suitable partition exists, an error will occur.

operations such as TRUNCATE which normally affect a table and all of its inheritance children will cascade to all partitions, but may also be performed on an individual partition. note that dropping a partition with DROP TABLE requires taking an ACCESS EXCLUSIVE lock on the parent table. plan accordingly, bestie 💀.

🦋 LIKE 🦋

LIKE source_table [ like_option ... ]

the LIKE clause specifies a table from which the new table automatically copies all column names, their data types, and their not-null constraints. it’s giving “copy my outfit but make it your own” ✨.

unlike INHERITS, the new table and original table are completely decoupled after creation is complete. changes to the original table will not be applied to the new table, and it is not possible to include data of the new table in scans of the original table. boundaries, periodt.

also unlike INHERITS, columns and constraints copied by LIKE are not merged with similarly named columns and constraints. if the same name is specified explicitly or in another LIKE clause, an error is signaled.

the optional like_option clauses specify which additional properties of the original table to copy. specifying INCLUDING copies the property, specifying EXCLUDING omits the property. EXCLUDING is the default. if multiple specifications are made for the same kind of object, the last one is used. the available options are:

  • INCLUDING COMMENTS — comments for the copied columns, constraints, and indexes will be copied. the default behavior is to exclude comments, resulting in the copied columns and constraints in the new table having no comments.
  • INCLUDING CONSTRAINTS — CHECK constraints will be copied. no distinction is made between column constraints and table constraints. not-null constraints are always copied to the new table 🌸.
  • INCLUDING DEFAULTS — okay so this one copies the default expressions from the copied column definitions 💖. If you don’t include it, those default expressions are not copied, and the copied columns in the new table just get null defaults. Tiny warning tho: copying defaults that call database-modification functions, like nextval, may create a functional linkage between the original table and the new table 👀.
  • INCLUDING GENERATED — any generation expressions from the copied column definitions get copied ✨. By default, new columns will be regular base columns.
  • INCLUDING IDENTITY — any identity specifications from the copied column definitions get copied 🎀. A new sequence is created for each identity column of the new table, and it’s separate from the sequences associated with the old table.
  • INCLUDING INDEXES — indexes, PRIMARY KEY, UNIQUE, and EXCLUDE constraints on the original table will be created on the new table 🔥. Names for the new indexes and constraints are chosen according to the default rules, regardless of how the originals were named. (This behavior avoids possible duplicate-name failures for the new indexes.)
  • INCLUDING STATISTICS — extended statistics are copied to the new table 📊.
  • INCLUDING STORAGE — STORAGE settings for the copied column definitions get copied 💾. The default behavior is to exclude STORAGE settings, which means the copied columns in the new table get type-specific default settings. For more on STORAGE settings, see Section 69.2.
  • INCLUDING ALL — this is the abbreviated form that selects all the available individual options 👑. (It could be useful to write individual EXCLUDING clauses after INCLUDING ALL to select all but some specific options.)

The LIKE clause can also be used to copy column definitions from views, foreign tables, or composite types 🦋. Inapplicable options (e.g., INCLUDING INDEXES from a view) are ignored.

💅 CONSTRAINT constraint_name

An optional name for a column or table constraint. If the constraint is violated, the constraint name is present in error messages, so constraint names like col must be positive can be used to communicate helpful constraint information to client applications 💖. (Double-quotes are needed to specify constraint names that contain spaces.) If a constraint name is not specified, the system generates a name.

💖 NOT NULL

The column is not allowed to contain null values. Periodt.

🌸 NULL

The column is allowed to contain null values. This is the default. This clause is only provided for compatibility with non-standard SQL databases, and its use is discouraged in new applications 🙈.

✨ CHECK ( expression ) [ NO INHERIT ]

The CHECK clause specifies an expression producing a Boolean result which new or updated rows must satisfy for an insert or update operation to succeed. Expressions evaluating to TRUE or UNKNOWN succeed ✅. If any row of an insert or update operation produces a FALSE result, an error exception is raised and the insert or update does not alter the database 💀. A check constraint specified as a column constraint should reference that column’s value only, while an expression appearing in a table constraint can reference multiple columns.

Currently, CHECK expressions cannot contain subqueries nor refer to variables other than columns of the current row (see Section 5.4.1). The system column tableoid may be referenced, but not any other system column 👀.

A constraint marked with NO INHERIT will not propagate to child tables.

When a table has multiple CHECK constraints, they will be tested for each row in alphabetical order by name, after checking NOT NULL constraints. (PostgreSQL versions before 9.5 did not honor any particular firing order for CHECK constraints.)

🎀 DEFAULT default_expr

The DEFAULT clause assigns a default data value for the column whose column definition it appears within 💖. The value is any variable-free expression (in particular, cross-references to other columns in the current table are not allowed). Subqueries are not allowed either. The data type of the default expression must match the data type of the column.

The default expression will be used in any insert operation that does not specify a value for the column. If there is no default for a column, then the default is null.

🦋 GENERATED ALWAYS AS ( generation_expr ) STORED

This clause creates the column as a generated column ✨. The column cannot be written to, and when read the result of the specified expression will be returned.

The keyword STORED is required to signify that the column will be computed on write and will be stored on disk 💾.

The generation expression can refer to other columns in the table, but not other generated columns. Any functions and operators used must be immutable. References to other tables are not allowed 🚫.

👑 GENERATED { ALWAYS | BY DEFAULT } AS IDENTITY [ ( sequence_options ) ]

This clause creates the column as an identity column 💅. It will have an implicit sequence attached to it and the column in new rows will automatically have values from the sequence assigned to it. Such a column is implicitly NOT NULL.

The clauses ALWAYS and BY DEFAULT determine how explicitly user-specified values are handled in INSERT and UPDATE commands.

In an INSERT command, if ALWAYS is selected, a user-specified value is only accepted if the INSERT statement specifies OVERRIDING SYSTEM VALUE. If BY DEFAULT is selected, then the user-specified value takes precedence. See INSERT(7) for details. (In the COPY command, user-specified values are always used regardless of this setting.)

In an UPDATE command, if ALWAYS is selected, any update of the column to any value other than DEFAULT will be rejected. If BY DEFAULT is selected, the column can be updated normally. (There is no OVERRIDING clause for the UPDATE command.)

The optional sequence_options clause can be used to override the options of the sequence. See CREATE SEQUENCE (CREATE_SEQUENCE(7)) for details.

🔥 UNIQUE

UNIQUE (column constraint)
UNIQUE ( column_name [, ... ] ) [ INCLUDE ( column_name [, ...]) ]
(table constraint)

The UNIQUE constraint specifies that a group of one or more columns of a table can contain only unique values 💖. The behavior of a unique table constraint is the same as that of a unique column constraint, with the additional capability to span multiple columns. The constraint therefore enforces that any two rows must differ in at least one of these columns.

For the purpose of a unique constraint, null values are not considered equal 👀.

Each unique constraint should name a set of columns that is different from the set of columns named by any other unique or primary key constraint defined for the table. (Otherwise, redundant unique constraints will be discarded.)

When establishing a unique constraint for a multi-level partition hierarchy, all the columns in the partition key of the target partitioned table, as well as those of all its descendant partitioned tables, must be included in the constraint definition.

Adding a unique constraint will automatically create a unique btree index on the column or group of columns used in the constraint 🌈.

The optional INCLUDE clause adds to that index one or more columns that are simply “payload”: uniqueness is not enforced on them, and the index cannot be searched on the basis of those columns. However they can be retrieved by an index-only scan. Note that although the constraint is not enforced on included columns, it still depends on them. Consequently, some operations on such columns (e.g., DROP COLUMN) can cause cascaded constraint and index deletion 💀.

⭐ PRIMARY KEY

PRIMARY KEY (column constraint)
PRIMARY KEY ( column_name [, ... ] ) [ INCLUDE ( column_name [, ...]) ]
(table constraint)

The PRIMARY KEY constraint specifies that a column or columns of a table can contain only unique (non-duplicate), nonnull values 👑. Only one primary key can be specified for a table, whether as a column constraint or a table constraint.

The primary key constraint should name a set of columns that is different from the set of columns named by any unique constraint defined for the same table. (Otherwise, the unique constraint is redundant and will be discarded.)

PRIMARY KEY enforces the same data constraints as a combination of UNIQUE and NOT NULL. However, identifying a set of columns as the primary key also provides metadata about the design of the schema, since a primary key implies that other tables can rely on this set of columns as a unique identifier for rows ✨.

When placed on a partitioned table, PRIMARY KEY constraints share the restrictions previously described for UNIQUE constraints.

Adding a PRIMARY KEY constraint will automatically create a unique btree index on the column or group of columns used in the constraint 💖.

The optional INCLUDE clause adds to that index one or more columns that are simply “payload”: uniqueness is not enforced on them, and the index cannot be searched on the basis of those columns. However they can be retrieved by an index-only scan. Note that although the constraint is not enforced on included columns, it still depends on them. Consequently, some operations on such columns (e.g., DROP COLUMN) can cause cascaded constraint and index deletion 💀.

🧚 EXCLUDE

EXCLUDE [ USING index_method ] ( exclude_element WITH operator [, ... ]
) index_parameters [ WHERE ( predicate ) ]

The EXCLUDE clause defines an exclusion constraint, which guarantees that if any two rows are compared on the specified column(s) or expression(s) using the specified operator(s), not all of these comparisons will return TRUE 🔥. If all of the specified operators test for equality, this is equivalent to a UNIQUE constraint, although an ordinary unique constraint will be faster. However, exclusion constraints can specify constraints that are more general than simple equality. For example, you can specify a constraint that no two rows in the table contain overlapping circles (see Section 8.8) by using the && operator. The operator(s) are required to be commutative.

ok so exclusion constraints are literally an index in a trench coat 🕵️‍♀️ — which means every operator you specify has to be paired up with an appropriate operator class (go peek at Section 11.10) for that index access method, index_method. And each exclude_element is basically defining a column of the index, so it can optionally carry a collation, an operator class, operator class parameters, and/or ordering options. All of that is spelled out in full under CREATE INDEX (CREATE_INDEX(7)).

🚩 the access method must support amgettuple (see Chapter 61) — which, as of right now, means GIN cannot be used. not a vibe, just facts.

And yeah, you're technically allowed to use B-tree or hash indexes with an exclusion constraint, but bestie, there is little point — because this does nothing that an ordinary unique constraint doesn't do better. So in practice the access method will always be GiST or SP-GiST. 💅

The predicate is how you slap an exclusion constraint onto just a subset of the table; internally that creates a partial index. 🎀 note that parentheses are required around the predicate, no exceptions.

🫶 the REFERENCES clause (foreign keys, the "your row better exist" situation)

REFERENCES reftable [ ( refcolumn ) ] [ MATCH matchtype ] [ ON DELETE
referential_action ] [ ON UPDATE referential_action ] (column
constraint)
FOREIGN KEY ( column_name [, ... ] ) REFERENCES reftable [ ( refcolumn
[, ... ] ) ] [ MATCH matchtype ] [ ON DELETE referential_action ] [ ON
UPDATE referential_action ] (table constraint)

These clauses specify a foreign key constraint, which requires that a group of one or more columns of the new table must only contain values that match values in the referenced column(s) of some row of the referenced table. 🦋

If the refcolumn list is omitted, the primary key of the reftable is used. Otherwise, the refcolumn list must refer to the columns of a non-deferrable unique or primary key constraint, or be the columns of a non-partial unique index. The user must have REFERENCES permission on the referenced table (either the whole table, or the specific referenced columns). Adding a foreign key constraint requires a SHARE ROW EXCLUSIVE lock on the referenced table. 🔒 And heads up: foreign key constraints cannot be defined between temporary tables and permanent tables. nope, not a thing.

A value inserted into the referencing column(s) gets matched against the values of the referenced table and referenced columns using the given match type. There are three match types — MATCH FULL, MATCH PARTIAL, and MATCH SIMPLE (which is the default):

  • MATCH FULL — will not allow one column of a multicolumn foreign key to be null unless all foreign key columns are null; and if they are all null, the row is not required to have a match in the referenced table.
  • MATCH SIMPLE — allows any of the foreign key columns to be null; if any of them are null, the row is not required to have a match in the referenced table.
  • MATCH PARTIAL — not yet implemented. 😭 don't come for me, it's just not.

(and of course, NOT NULL constraints can be applied to the referencing column(s) to prevent these cases from arising — iykyk ✨)

In addition, when the data in the referenced columns is changed, certain actions are performed on the data in this table's columns. The ON DELETE clause says what to do when a referenced row in the referenced table is being deleted. Likewise, the ON UPDATE clause says what to do when a referenced column in the referenced table is being updated to a new value. If the row is updated but the referenced column is not actually changed, no action is done. 🫠

⚠️ referential actions other than the NO ACTION check cannot be deferred, even if the constraint is declared deferrable. like, that's just how it is.

There are the following possible actions for each clause:

  • NO ACTION — produce an error indicating that the deletion or update would create a foreign key constraint violation. If the constraint is deferred, this error will be produced at constraint check time if there still exist any referencing rows. This is the default action.
  • RESTRICT — produce an error indicating that the deletion or update would create a foreign key constraint violation. This is the same as NO ACTION except that the check is not deferrable.
  • CASCADE — delete any rows referencing the deleted row, or update the values of the referencing column(s) to the new values of the referenced columns, respectively. 💥
  • SET NULL — set the referencing column(s) to null.
  • SET DEFAULT — set the referencing column(s) to their default values. (there must be a row in the referenced table matching the default values, if they are not null, or the operation will fail. 🙈)

If the referenced column(s) are changed frequently, it might be wise to add an index to the referencing column(s) so that referential actions associated with the foreign key constraint can be performed more efficiently. 📈 little glow-up, big payoff.

💜 DEFERRABLE / NOT DEFERRABLE

This controls whether the constraint can be deferred. A constraint that is not deferrable will be checked immediately after every command. Checking of constraints that are deferrable can be postponed until the end of the transaction (using the SET CONSTRAINTS (SET_CONSTRAINTS(7)) command). NOT DEFERRABLE is the default.

Currently, only UNIQUE, PRIMARY KEY, EXCLUDE, and REFERENCES (foreign key) constraints accept this clause. NOT NULL and CHECK constraints are not deferrable. 🚫

⚠️ also note: deferrable constraints cannot be used as conflict arbitrators in an INSERT statement that includes an ON CONFLICT DO UPDATE clause.

🌸 INITIALLY IMMEDIATE / INITIALLY DEFERRED

If a constraint is deferrable, this clause specifies the default time to check it:

  • INITIALLY IMMEDIATE — checked after each statement. This is the default.
  • INITIALLY DEFERRED — checked only at the end of the transaction.

The constraint check time can be altered with the SET CONSTRAINTS (SET_CONSTRAINTS(7)) command. 🎀

🦋 USING method

This optional clause specifies the table access method to use to store the contents for the new table; the method needs be an access method of type TABLE. See Chapter 60 for more information. If this option is not specified, the default table access method is chosen for the new table. See default_table_access_method for more information. ✨

📦 WITH ( storage_parameter [= value] [, ... ] )

This clause specifies optional storage parameters for a table or index; see Storage Parameters below for more information. For backward-compatibility, the WITH clause for a table can also include OIDS=FALSE to specify that rows of the new table should not contain OIDs (object identifiers). OIDS=TRUE is not supported anymore. 👋

WITHOUT OIDS

This is backward-compatible syntax for declaring a table WITHOUT OIDS. Creating a table WITH OIDS is not supported anymore. 💀

🎀 ON COMMIT

The behavior of temporary tables at the end of a transaction block can be controlled using ON COMMIT. The three options are:

  • PRESERVE ROWS — no special action is taken at the ends of transactions. This is the default behavior.
  • DELETE ROWS — all rows in the temporary table will be deleted at the end of each transaction block. Essentially, an automatic TRUNCATE(7) is done at each commit. When used on a partitioned table, this is not cascaded to its partitions. 🧹
  • DROP — the temporary table will be dropped at the end of the current transaction block. When used on a partitioned table, this action drops its partitions, and when used on tables with inheritance children, it drops the dependent children. 💀

TABLESPACE tablespace_name

The tablespace_name is the name of the tablespace in which the new table is to be created. If not specified, default_tablespace is consulted, or temp_tablespaces if the table is temporary.

For partitioned tables, since no storage is required for the table itself, the tablespace specified overrides default_tablespace as the default tablespace to use for any newly created partitions when no other tablespace is explicitly specified. 🗂️

USING INDEX TABLESPACE tablespace_name

This clause allows selection of the tablespace in which the index associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint will be created. If not specified, default_tablespace is consulted, or temp_tablespaces if the table is temporary.

📦 Storage Parameters (yes, the storage-y ones)

The WITH clause can specify storage parameters for tables, and for indexes associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint. Storage parameters for indexes are documented in CREATE INDEX (CREATE_INDEX(7)). The storage parameters currently available for tables are listed below. 👇

For many of these parameters, as shown, there is an additional parameter with the same name prefixed with toast., which controls the behavior of the table's secondary TOAST table, if any (see Section 69.2 for more information about TOAST). If a table parameter value is set and the equivalent toast. parameter is not, the TOAST table will use the table's parameter value. 🍞

ngl, specifying these parameters for partitioned tables is not supported — but you may specify them for individual leaf partitions. 🌱

fillfactor (integer)

The fillfactor for a table is a percentage between 10 and 100. 100 (complete packing) is the default. When a smaller fillfactor is specified, INSERT operations pack table pages only to the indicated percentage; the remaining space on each page is reserved for updating rows on that page. This gives UPDATE a chance to place the updated copy of a row on the same page as the original, which is more efficient than placing it on a different page, and makes heap-only tuple updates more likely. 🔥

For a table whose entries are never updated, complete packing is the best choice, but in heavily updated tables smaller fillfactors are appropriate. This parameter cannot be set for TOAST tables. 🙅‍♀️

  • toast_tuple_target (integer) — this one sets the minimum tuple length that has to be hit before Postgres even thinks about compressing and/or yeeting your long column values into TOAST tables 🍞, and it's also the target length it tries to squeeze things down under once toasting kicks off. It touches columns marked External (for the move), Main (for the compression), or Extended (for both) — and it only applies to new tuples, so existing rows are literally unaffected, no cap. Default is set so you get at least 4 tuples per block, which with the default block size comes out to 2040 bytes. Valid values live between 128 bytes and the (block size - header), which by default is 8160 bytes. Changing this might not even be useful for super short or super long rows, and honestly the default is often close to optimal already, so it's very possible setting this could have negative effects in some cases 😭. Also: this parameter cannot be set for TOAST tables, periodt.
  • parallel_workers (integer) — sets how many workers should help out with a parallel scan of this table. If you don't set it, the system picks a value based on the relation size. The actual number of workers the planner (or utility statements using parallel scans) ends up choosing may be less — for example because of how max_worker_processes is set. Budget cuts, bestie 💅
  • autovacuum_enabled, toast.autovacuum_enabled (boolean) — turns the autovacuum daemon on or off for one specific table. If true, the daemon will do automatic VACUUM and/or ANALYZE operations on this table following the rules from Section 24.1.6. If false, this table won't be autovacuumed — except to prevent transaction ID wraparound (Section 24.1.5 has the lore on wraparound prevention). Big heads up: the autovacuum daemon doesn't run at all (again, except for wraparound prevention) if the autovacuum parameter is false, and setting individual tables' storage parameters does not override that. So there's seldom much point in explicitly setting this to true — only to false. It's giving "off switch only" 🚫
  • vacuum_index_cleanup, toast.vacuum_index_cleanup (boolean) — enables or disables index cleanup when VACUUM runs on this table. Default is true. Disabling index cleanup can speed up VACUUM very significantly, but it may also lead to severely bloated indexes if the table gets modified a lot 😬. The INDEX_CLEANUP parameter of VACUUM(7), if you specify it, overrides this option.
  • vacuum_truncate, toast.vacuum_truncate (boolean) — lets VACUUM try to truncate off any empty pages hanging out at the end of this table. Default is true. If true, VACUUM and autovacuum do the truncation and the disk space for those pages goes back to the operating system 🎁. Note that truncation requires an ACCESS EXCLUSIVE lock on the table — so yeah, keep that in mind. The TRUNCATE parameter of VACUUM(7), if specified, overrides this option.
  • autovacuum_vacuum_threshold, toast.autovacuum_vacuum_threshold (integer) — per-table value for the autovacuum_vacuum_threshold parameter.
  • autovacuum_vacuum_scale_factor, toast.autovacuum_vacuum_scale_factor (floating point) — per-table value for the autovacuum_vacuum_scale_factor parameter.
  • autovacuum_vacuum_insert_threshold, toast.autovacuum_vacuum_insert_threshold (integer) — per-table value for the autovacuum_vacuum_insert_threshold parameter. Special value -1 can be used to disable insert vacuums on the table ✨
  • autovacuum_vacuum_insert_scale_factor, toast.autovacuum_vacuum_insert_scale_factor (floating point) — per-table value for the autovacuum_vacuum_insert_scale_factor parameter.
  • autovacuum_analyze_threshold (integer) — per-table value for the autovacuum_analyze_threshold parameter.
  • autovacuum_analyze_scale_factor (floating point) — per-table value for the autovacuum_analyze_scale_factor parameter.
  • autovacuum_vacuum_cost_delay, toast.autovacuum_vacuum_cost_delay (floating point) — per-table value for the autovacuum_vacuum_cost_delay parameter.
  • autovacuum_vacuum_cost_limit, toast.autovacuum_vacuum_cost_limit (integer) — per-table value for the autovacuum_vacuum_cost_limit parameter.
  • autovacuum_freeze_min_age, toast.autovacuum_freeze_min_age (integer) — per-table value for the vacuum_freeze_min_age parameter. Heads up though: autovacuum will ignore per-table autovacuum_freeze_min_age parameters that are larger than half the system-wide autovacuum_freeze_max_age setting 👀
  • autovacuum_freeze_max_age, toast.autovacuum_freeze_max_age (integer) — per-table value for the autovacuum_freeze_max_age parameter. Same deal: autovacuum will ignore per-table autovacuum_freeze_max_age parameters that are larger than the system-wide setting (it can only be set smaller, no glow-ups allowed).
  • autovacuum_freeze_table_age, toast.autovacuum_freeze_table_age (integer) — per-table value for the vacuum_freeze_table_age parameter.
  • autovacuum_multixact_freeze_min_age, toast.autovacuum_multixact_freeze_min_age (integer) — per-table value for the vacuum_multixact_freeze_min_age parameter. And yep, autovacuum will ignore per-table autovacuum_multixact_freeze_min_age parameters that are larger than half the system-wide autovacuum_multixact_freeze_max_age setting 🫠
  • autovacuum_multixact_freeze_max_age, toast.autovacuum_multixact_freeze_max_age (integer) — per-table value for the autovacuum_multixact_freeze_max_age parameter. Autovacuum will ignore per-table autovacuum_multixact_freeze_max_age parameters that are larger than the system-wide setting (it can only be set smaller).
  • autovacuum_multixact_freeze_table_age, toast.autovacuum_multixact_freeze_table_age (integer) — per-table value for the vacuum_multixact_freeze_table_age parameter.
  • log_autovacuum_min_duration, toast.log_autovacuum_min_duration (integer) — per-table value for the log_autovacuum_min_duration parameter.
  • user_catalog_table (boolean) — declares the table as an additional catalog table for purposes of logical replication (Section 48.6.2 has the details). This parameter cannot be set for TOAST tables 🚫

🌸 NOTES 🌸

Okay so this next part is the stuff that will lowkey save you later, bestie:

PostgreSQL automatically creates an index for each unique constraint and primary key constraint so it can enforce uniqueness. Which means — plot twist — it is not necessary to create an index explicitly for primary key columns 💅 (peep CREATE INDEX — CREATE_INDEX(7) — if you want more on that).

Unique constraints and primary keys are not inherited in the current implementation. So the combo of inheritance and unique constraints is, ngl, rather dysfunctional 😭 fr fr.

And a table cannot have more than 1600 columns. (In practice the effective limit is usually lower anyway because of tuple-length constraints, so don't get too comfy 🫶)

✨ EXAMPLES ✨

okay bestie, this is the show-and-tell section and honestly it ate 💅 we’re gonna walk through every single example, no skips, no cap.

Create table films and table distributors:

           CREATE TABLE films (
               code        char(5) CONSTRAINT firstkey PRIMARY KEY,
               title       varchar(40) NOT NULL,
               did         integer NOT NULL,
               date_prod   date,
               kind        varchar(10),
               len         interval hour to minute
           );

           CREATE TABLE distributors (
                did    integer PRIMARY KEY GENERATED BY DEFAULT AS IDENTITY,
                name   varchar(40) NOT NULL CHECK (name <> '')
           );

Create a table with a 2-dimensional array: 🧊✨

           CREATE TABLE array_int (
               vector  int[][]
           );

Define a unique table constraint for the table films. Unique table constraints can be defined on one or more columns of the table, and yes that’s the whole vibe 👑

           CREATE TABLE films (
               code        char(5),
               title       varchar(40),
               did         integer,
               date_prod   date,
               kind        varchar(10),
               len         interval hour to minute,
               CONSTRAINT production UNIQUE(date_prod)
           );

Define a check column constraint: 🎀

           CREATE TABLE distributors (
               did     integer CHECK (did > 100),
               name    varchar(40)
           );

Define a check table constraint: 🫶

           CREATE TABLE distributors (
               did     integer,
               name    varchar(40),
               CONSTRAINT con1 CHECK (did > 100 AND name <> '')
           );

Define a primary key table constraint for the table films: 🔑

           CREATE TABLE films (
               code        char(5),
               title       varchar(40),
               did         integer,
               date_prod   date,
               kind        varchar(10),
               len         interval hour to minute,
               CONSTRAINT code_title PRIMARY KEY(code,title)
           );

Define a primary key constraint for table distributors. The following two examples are equivalent, bestie — the first uses the table constraint syntax, the second uses the column constraint syntax 💖

           CREATE TABLE distributors (
               did     integer,
               name    varchar(40),
               PRIMARY KEY(did)
           );

           CREATE TABLE distributors (
               did     integer PRIMARY KEY,
               name    varchar(40)
           );

Assign a literal constant default value for the column name, arrange for the default value of column did to be generated by selecting the next value of a sequence object, and make the default value of modtime be the time at which the row is inserted: ⏰✨

           CREATE TABLE distributors (
               name      varchar(40) DEFAULT 'Luso Films',
               did       integer DEFAULT nextval('distributors_serial'),
               modtime   timestamp DEFAULT current_timestamp
           );

Define two NOT NULL column constraints on the table distributors, one of which is explicitly given a name: 🚫

           CREATE TABLE distributors (
               did     integer CONSTRAINT no_null NOT NULL,
               name    varchar(40) NOT NULL
           );

Define a unique constraint for the name column: 🌸

           CREATE TABLE distributors (
               did     integer,
               name    varchar(40) UNIQUE
           );

The same, specified as a table constraint: 🦋

           CREATE TABLE distributors (
               did     integer,
               name    varchar(40),
               UNIQUE(name)
           );

Create the same table, specifying 70% fill factor for both the table and its unique index: 🌈

           CREATE TABLE distributors (
               did     integer,
               name    varchar(40),
               UNIQUE(name) WITH (fillfactor=70)
           )
           WITH (fillfactor=70);

Create table circles with an exclusion constraint that prevents any two circles from overlapping: ⭕💀

           CREATE TABLE circles (
               c circle,
               EXCLUDE USING gist (c WITH &&)
           );

Create table cinemas in tablespace diskvol1: 🎬

           CREATE TABLE cinemas (
                   id serial,
                   name text,
                   location text
           ) TABLESPACE diskvol1;

Create a composite type and a typed table: 🧚

           CREATE TYPE employee_type AS (name text, salary numeric);

           CREATE TABLE employees OF employee_type (
               PRIMARY KEY (name),
               salary WITH OPTIONS DEFAULT 1000
           );

Create a range partitioned table: 📊

           CREATE TABLE measurement (
               logdate         date not null,
               peaktemp        int,
               unitsales       int
           ) PARTITION BY RANGE (logdate);

Create a range partitioned table with multiple columns in the partition key: 🔥

           CREATE TABLE measurement_year_month (
               logdate         date not null,
               peaktemp        int,
               unitsales       int
           ) PARTITION BY RANGE (EXTRACT(YEAR FROM logdate), EXTRACT(MONTH FROM logdate));

Create a list partitioned table: 💜

           CREATE TABLE cities (
               city_id      bigserial not null,
               name         text not null,
               population   bigint
           ) PARTITION BY LIST (left(lower(name), 1));

Create a hash partitioned table: 🎀

           CREATE TABLE orders (
               order_id     bigint not null,
               cust_id      bigint not null,
               status       text
           ) PARTITION BY HASH (order_id);

Create partition of a range partitioned table: 🧊

           CREATE TABLE measurement_y2016m07
               PARTITION OF measurement (
               unitsales DEFAULT 0
           ) FOR VALUES FROM ('2016-07-01') TO ('2016-08-01');

Create a few partitions of a range partitioned table with multiple columns in the partition key: 🌟

           CREATE TABLE measurement_ym_older
               PARTITION OF measurement_year_month
               FOR VALUES FROM (MINVALUE, MINVALUE) TO (2016, 11);

           CREATE TABLE measurement_ym_y2016m11
               PARTITION OF measurement_year_month
               FOR VALUES FROM (2016, 11) TO (2016, 12);

           CREATE TABLE measurement_ym_y2016m12
               PARTITION OF measurement_year_month
               FOR VALUES FROM (2016, 12) TO (2017, 01);

           CREATE TABLE measurement_ym_y2017m01
               PARTITION OF measurement_year_month
               FOR VALUES FROM (2017, 01) TO (2017, 02);

Create partition of a list partitioned table: 🌸

           CREATE TABLE cities_ab
               PARTITION OF cities (
               CONSTRAINT city_id_nonzero CHECK (city_id != 0)
           ) FOR VALUES IN ('a', 'b');

Create partition of a list partitioned table that is itself further partitioned and then add a partition to it: 🦋✨

           CREATE TABLE cities_ab
               PARTITION OF cities (
               CONSTRAINT city_id_nonzero CHECK (city_id != 0)
           ) FOR VALUES IN ('a', 'b') PARTITION BY RANGE (population);

           CREATE TABLE cities_ab_10000_to_100000
               PARTITION OF cities_ab FOR VALUES FROM (10000) TO (100000);

Create partitions of a hash partitioned table: 🌈

           CREATE TABLE orders_p1 PARTITION OF orders
               FOR VALUES WITH (MODULUS 4, REMAINDER 0);
           CREATE TABLE orders_p2 PARTITION OF orders
               FOR VALUES WITH (MODULUS 4, REMAINDER 1);
           CREATE TABLE orders_p3 PARTITION OF orders
               FOR VALUES WITH (MODULUS 4, REMAINDER 2);
           CREATE TABLE orders_p4 PARTITION OF orders
               FOR VALUES WITH (MODULUS 4, REMAINDER 3);

Create a default partition: 💖

           CREATE TABLE cities_partdef
               PARTITION OF cities DEFAULT;

💖 COMPATIBILITY 💖

Okay so CREATE TABLE conforms to the SQL standard, bestie — but there are exceptions, and they are literally listed right below. No cap.

🌸 Temporary Tables 🌸

The syntax of CREATE TEMPORARY TABLE looks like the SQL standard, but the effect is not the same. In the standard, temporary tables are defined just once and automatically exist — starting with empty contents — in every session that needs them. PostgreSQL instead requires each session to issue its own CREATE TEMPORARY TABLE command for each temporary table to be used. This lets different sessions use the same temporary table name for different purposes, whereas the standard’s approach constrains all instances of a given temporary table name to have the same table structure.

The standard’s definition of temporary-table behavior is widely ignored. PostgreSQL’s behavior on this point is similar to that of several other SQL databases.

The SQL standard also distinguishes between global and local temporary tables, where a local temporary table has a separate set of contents for each SQL module within each session, though its definition is still shared across sessions. Since PostgreSQL does not support SQL modules, this distinction is not relevant in PostgreSQL.

For compatibility’s sake, PostgreSQL will accept the GLOBAL and LOCAL keywords in a temporary table declaration, but they currently have no effect.

Use of these keywords is discouraged, since future versions of PostgreSQL might adopt a more standard-compliant interpretation of their meaning. 👀

The ON COMMIT clause for temporary tables also resembles the SQL standard, but has some differences. If the ON COMMIT clause is omitted, SQL specifies that the default behavior is ON COMMIT DELETE ROWS. However, the default behavior in PostgreSQL is ON COMMIT PRESERVE ROWS. The ON COMMIT DROP option does not exist in SQL.

💅 Non-Deferred Uniqueness Constraints 💅

When a UNIQUE or PRIMARY KEY constraint is not deferrable, PostgreSQL checks for uniqueness immediately whenever a row is inserted or modified. The SQL standard says that uniqueness should be enforced only at the end of the statement; this makes a difference when, for example, a single command updates multiple key values. To obtain standard-compliant behavior, declare the constraint as DEFERRABLE but not deferred (i.e., INITIALLY IMMEDIATE).

Be aware that this can be significantly slower than immediate uniqueness checking. 😭

🎀 Column Check Constraints 🎀

The SQL standard says that CHECK column constraints can only refer to the column they apply to; only CHECK table constraints can refer to multiple columns. PostgreSQL does not enforce this restriction — it treats column and table check constraints alike.

🦋 EXCLUDE Constraint 🦋

The EXCLUDE constraint type is a PostgreSQL extension.

🔥 Foreign Key Constraints 🔥

It is a PostgreSQL extension that a foreign key constraint may reference columns of a unique index instead of columns of a primary key or unique constraint.

👑 NULL “Constraint” 👑

The NULL “constraint” (actually a non-constraint) is a PostgreSQL extension to the SQL standard that is included for compatibility with some other database systems (and for symmetry with the NOT NULL constraint). Since it is the default for any column, its presence is simply noise.

⭐ Constraint Naming ⭐

The SQL standard says that table and domain constraints must have names that are unique across the schema containing the table or domain. PostgreSQL is laxer: it only requires constraint names to be unique across the constraints attached to a particular table or domain. However, this extra freedom does not exist for index-based constraints (UNIQUE, PRIMARY KEY, and EXCLUDE constraints), because the associated index is named the same as the constraint, and index names must be unique across all relations within the same schema.

Currently, PostgreSQL does not record names for NOT NULL constraints at all, so they are not subject to the uniqueness restriction. This might change in a future release.

🌈 Inheritance 🌈

Multiple inheritance via the INHERITS clause is a PostgreSQL language extension. SQL:1999 and later define single inheritance using a different syntax and different semantics. SQL:1999-style inheritance is not yet supported by PostgreSQL.

💀 Zero-Column Tables 💀

PostgreSQL allows a table of no columns to be created (for example, CREATE TABLE foo();). This is an extension from the SQL standard, which does not allow zero-column tables. Zero-column tables are not in themselves very useful, but disallowing them creates odd special cases for ALTER TABLE DROP COLUMN, so it seems cleaner to ignore this spec restriction.

🫶 Multiple Identity Columns 🫶

PostgreSQL allows a table to have more than one identity column. The standard specifies that a table can have at most one identity column. This is relaxed mainly to give more flexibility for doing schema changes or migrations. Note that the INSERT command supports only one override clause that applies to the entire statement, so having multiple identity columns with different behaviors is not well supported.

🍓 Generated Columns 🍓

The option STORED is not standard but is also used by other SQL implementations. The SQL standard does not specify the storage of generated columns.

🧚 LIKE Clause 🧚

While a LIKE clause exists in the SQL standard, many of the options that PostgreSQL accepts for it are not in the standard, and some of the standard’s options are not implemented by PostgreSQL.

💜 WITH Clause 💜

The WITH clause is a PostgreSQL extension; storage parameters are not in the standard.

✨ Tablespaces ✨

The PostgreSQL concept of tablespaces is not part of the standard. Hence, the clauses TABLESPACE and USING INDEX TABLESPACE are extensions.

🌸 Typed Tables 🌸

Typed tables implement a subset of the SQL standard. According to the standard, a typed table has columns corresponding to the underlying composite type as well as one other column that is the “self-referencing column”. PostgreSQL does not support self-referencing columns explicitly.

🎀 PARTITION BY Clause 🎀

The PARTITION BY clause is a PostgreSQL extension.

🦋 PARTITION OF Clause 🦋

The PARTITION OF clause is a PostgreSQL extension.

👀 SEE ALSO 👀

That’s the whole vibe check, bestie — this page is from PostgreSQL 13.23, dated 2025, and it’s the CREATE TABLE(7) page. Mwah 💋✨

📦 where this page comes from