CREATE_TABLE(7)

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version 18.6 · 20 versions
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💖 CREATE_TABLE(7) — PostgreSQL 18.6 Documentation 💖

okay bestie, sit down, hydrate, because we're about to learn how to make a whole entire table. this is the CREATE TABLE page, and it's a long one, so we're doing it in parts. part 1, let's go 🫶

✨ NAME ✨

CREATE_TABLE — define a new table. that's it, that's the vibe. you're literally building a little home for your rows 🏠

🌸 SYNOPSIS 🌸

CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } | UNLOGGED ] TABLE [ IF NOT EXISTS ] table_name ( [
  { column_name data_type [ STORAGE { PLAIN | EXTERNAL | EXTENDED | MAIN | DEFAULT } ] [ COMPRESSION compression_method ] [ 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 [ NO INHERIT ]  |
  NULL |
  CHECK ( expression ) [ NO INHERIT ] |
  DEFAULT default_expr |
  GENERATED ALWAYS AS ( generation_expr ) [ STORED | VIRTUAL ] |
  GENERATED { ALWAYS | BY DEFAULT } AS IDENTITY [ ( sequence_options ) ] |
  UNIQUE [ NULLS [ NOT ] DISTINCT ] 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 ] [ ENFORCED | NOT ENFORCED ]

and table_constraint is:

[ CONSTRAINT constraint_name ]
{ CHECK ( expression ) [ NO INHERIT ] |
  NOT NULL column_name [ NO INHERIT ] |
  UNIQUE [ NULLS [ NOT ] DISTINCT ] ( column_name [, ... ] [, column_name WITHOUT OVERLAPS ] ) index_parameters |
  PRIMARY KEY ( column_name [, ... ] [, column_name WITHOUT OVERLAPS ] ) index_parameters |
  EXCLUDE [ USING index_method ] ( exclude_element WITH operator [, ... ] ) index_parameters [ WHERE ( predicate ) ] |
  FOREIGN KEY ( column_name [, ... ] [, PERIOD column_name ] ) REFERENCES reftable [ ( refcolumn [, ... ] [, PERIOD refcolumn ] ) ]
    [ MATCH FULL | MATCH PARTIAL | MATCH SIMPLE ] [ ON DELETE referential_action ] [ ON UPDATE referential_action ] }
[ DEFERRABLE | NOT DEFERRABLE ] [ INITIALLY DEFERRED | INITIALLY IMMEDIATE ] [ ENFORCED | NOT ENFORCED ]

and like_option is:

{ INCLUDING | EXCLUDING } { COMMENTS | COMPRESSION | 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 } ]

referential_action in a FOREIGN KEY/REFERENCES constraint is:

{ NO ACTION | RESTRICT | CASCADE | SET NULL [ ( column_name [, ... ] ) ] | SET DEFAULT [ ( column_name [, ... ] ) ] }

🦋 DESCRIPTION 🦋

so CREATE TABLE makes a brand new, initially empty table in the current database. and who owns it? whoever ran the command, bestie. you made it, you own it 👑

if you give a schema name (like CREATE TABLE myschema.mytable ...) then the table gets created in that schema. no schema name? it goes in the current schema. temporary tables live in their own special schema, so you literally can't give a schema name when you're making a temporary table. and the table's name has to be distinct from every other relation in the same schema — table, sequence, index, view, materialized view, or foreign table. no name-stealing, periodt 💅

here's the sneaky part: CREATE TABLE also automatically creates a data type that represents the composite type matching one row of the table. so that means tables can't share a name with any existing data type in the same schema either. the way it does two things at once… multitasking icon behavior ✨

the optional constraint clauses are the "tests" — the rules that new or updated rows have to satisfy for an insert or update to actually succeed. a constraint is an SQL object that helps define the set of valid values in the table, in various ways.

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 isn't tied to a particular column and can cover more than one column. and here's the cute part — every column constraint can also be written as a table constraint. a column constraint is only a notational convenience for when the constraint only affects one column. lowkey it's the same thing in a different outfit 💅

and to be able to create a table, you must have USAGE privilege on all column types, or on the type in the OF clause, respectively. no privilege, no table, sorry bestie 😭

🎀 PARAMETERS 🎀

  • TEMPORARY or TEMP — if you specify this, the table is created as a temporary table. temporary tables get automatically dropped at the end of a session, or optionally at the end of the current transaction (peep ON COMMIT below). the default search_path includes the temporary schema first, so identically named existing permanent tables are not chosen for new plans while the temporary table exists — unless they're referenced with schema-qualified names. any indexes created on a temporary table are automatically temporary too.
😭 real talk: the autovacuum daemon cannot access temporary tables, so it can't vacuum or analyze them. 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. so like, write it if you want, it's giving nothing 🫠

  • 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 28), 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 this is specified, any sequences created together with the unlogged table (for identity or serial columns) are also created as unlogged.

⚠️ this form is not supported for partitioned tables. noted, bestie.
  • IF NOT EXISTS — don't 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. it's giving "sure, whatever's there, we move on" 🙈
  • table_name — the name (optionally schema-qualified) of the table to be created. simple as that ✨
  • OF type_name — creates a typed table, which takes its structure from the specified stand-alone composite type (that is, one created using CREATE TYPE (CREATE_TYPE(7))) — though it still produces a new composite type as well. the table will have a dependency on the referenced type, meaning that cascaded alter and drop actions on that type will propagate to the table.

a typed table always has the same column names and data types as the type it is derived from, so you cannot specify additional columns. but the CREATE TABLE command can add defaults and constraints to the table, as well as specify storage parameters. so you get the skeleton from the type and then you decorate 🎀

  • 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 info on the data types PostgreSQL supports, 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.
  • STORAGE { PLAIN | EXTERNAL | EXTENDED | MAIN | DEFAULT } — this form sets the storage mode for the column. it controls whether this column is held inline or in a secondary TOAST table, and whether the data should be compressed or not.
    • PLAIN must be used for fixed-length values such as integer, and it's inline, uncompressed.
    • MAIN is for inline, compressible data.
    • EXTERNAL is for external, uncompressed data.
    • EXTENDED is for external, compressed data.
    • writing DEFAULT sets the storage mode to the default mode for the column's data type.

EXTENDED is the default for most data types that support non-PLAIN storage. use of EXTERNAL will make substring operations on very large text and bytea values run faster, at the penalty of increased storage space. see Section 66.2 for more information. tradeoffs, bestie, it's always tradeoffs 💀

COMPRESSION 💾

COMPRESSION compression_method — this one sets the compression method for the column, bestie.

Real talk: compression is only supported for variable-width data types, and it only actually kicks in when the column's storage mode is main or extended. (Go check ALTER TABLE (ALTER_TABLE(7)) for the whole tea on column storage modes.)

Setting this on a partitioned table? No direct effect, because partitioned tables have no storage of their own — but the configured value will be inherited by newly-created partitions, so it's not wasted, bestie.

The supported compression methods are:

  • pglz
  • lz4

(heads up: lz4 is available only if --with-lz4 was used when building PostgreSQL, so vibe check your build first)

Also, compression_method can be default to explicitly specify the default behavior — which is to consult the default_toast_compression setting at the time of data insertion to determine the method to use. It's giving "decide later" energy and honestly? valid.

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 — no gatekeeping.

Using 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). Family runs deep, fr fr.

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's 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. No picky parents allowed.

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. She's independent like that. 💅

Column STORAGE settings are also copied from parent tables.

One more thing: 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 — so you can build your own identity, main character energy. ✨

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

The optional PARTITION BY clause specifies a strategy of partitioning the table. The table thus created is called a partitioned table.

The parenthesized list of columns or expressions forms the partition key for the table.

  • When using range or hash partitioning, the partition key can include multiple columns or expressions — up to 32, but this limit can be altered when building PostgreSQL.
  • For list partitioning, the partition key must consist of a single column or expression. One and only one, no plus-ones. 🙈

Range and list partitioning require a btree operator class, while hash partitioning requires a hash operator class. If no operator class is specified explicitly, the default operator class of the appropriate type will be used; if no default operator class exists, an error will be raised.

When hash partitioning is used, the operator class used must implement support function 2 (see Section 36.16.3 for details).

A partitioned table is divided into sub-tables (called partitions), which are created using separate CREATE TABLE commands. The partitioned table is itself empty. 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.

See Section 5.12 for more discussion on table partitioning.

PARTITION OF parent_table { FOR VALUES partition_bound_spec | DEFAULT } 🎀

Creates the table as a partition of the specified parent table. 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. Inheritance really said "copy paste but make it legal". 🔥

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. She's frozen in time, iconic. ⭐

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 9.25.5).

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.

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). 💀

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. She's the catch-all bestie.

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.

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. Incremental glow-up, we love to see it. 🦋

A partition has to match its partitioned table exactly — same column names, same types, no negotiating. 💅 And here's the slay part: if you change the column names or types on the partitioned table, that change automatically propagates to all the partitions. CHECK constraints get inherited automatically by every partition too, but an individual partition is allowed to add its own extra CHECK constraints; if an extra constraint has the same name and the same condition as the one in the parent, it gets merged with the parent constraint. Defaults, though? Those you can specify separately per partition. ⚠️ But heads up bestie: a partition's default value is not applied when inserting a tuple through a partitioned table. Not me finding that out the hard way.

Rows you insert into a partitioned table get automatically routed to the correct partition. If no suitable partition exists, you get an error. Periodt. 💀

Operations like TRUNCATE that normally hit a table and all of its inheritance children will cascade to all partitions — but you can also run them on an individual partition if that's the vibe. ✨

📌 Real talk: creating a partition with PARTITION OF requires taking an ACCESS EXCLUSIVE lock on the parent partitioned table. Same energy for dropping a partition with DROP TABLE — that also needs an ACCESS EXCLUSIVE lock on the parent table. You can use ALTER TABLE ATTACH/DETACH PARTITION to do these operations with a weaker lock instead, which reduces interference with concurrent operations on the partitioned table. Iconic workaround, lowkey.

🦋 LIKE source_table [ like_option ... ]

The LIKE clause names a table for the new table to copy stuff from — automatically grabbing all the column names, their data types, and their not-null constraints. Free real estate. 🎀

Unlike INHERITS, the new table and the original table are completely decoupled once creation is done. Changes to the original table will not be applied to the new table, and you cannot include data from the new table in scans of the original table. They're not in each other's group chats anymore. 🚫

Also unlike INHERITS: columns and constraints copied by LIKE are not merged with similarly named columns and constraints. If the same name shows up explicitly or in another LIKE clause, an error is signaled. No merging, no blending, we don't do that here. 😤

The optional like_option clauses say which additional properties of the original table to copy. Saying INCLUDING copies the property, saying EXCLUDING omits it. EXCLUDING is the default. If you make multiple specifications for the same kind of object, the last one wins. The available options are:

✨ INCLUDING COMMENTS

Comments for the copied columns, check constraints, not-null constraints, indexes, and extended statistics will be copied. The default behavior is to exclude comments, which means the corresponding objects in the new table have no comments at all. Silent. Empty. 🙈

✨ INCLUDING COMPRESSION

Compression method of the columns will be copied. The default behavior is to exclude compression methods, which means the columns just get the default compression method.

✨ 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 regardless — those come along for the ride whether you ask or not. 💁

✨ INCLUDING DEFAULTS

Default expressions for the copied column definitions will be copied. Otherwise, default expressions are not copied, which means the copied columns in the new table just have null defaults.

⚠️ Note that copying defaults that call database-modification functions, such as nextval, may create a functional linkage between the original and new tables. Be careful, bestie, that's a situationship.

✨ INCLUDING GENERATED

Any generation expressions as well as the stored/virtual choice of copied column definitions will be copied. By default, new columns will be regular base columns.

✨ INCLUDING IDENTITY

Any identity specifications of copied column definitions will be copied. A new sequence is created for each identity column of the new table, separate from the sequences associated with the old table. Fresh sequence, fresh start, new era. 🦋

✨ 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.) Thank you for your service. 🫶

✨ INCLUDING STATISTICS

Extended statistics are copied to the new table.

✨ INCLUDING STORAGE

STORAGE settings for the copied column definitions will be 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 66.2.

✨ INCLUDING ALL

INCLUDING ALL is an abbreviated form selecting 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 "everything bagel" of clauses, truly. 🥯

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. No error, just ignored. She's unbothered. 💅

🎀 CONSTRAINT constraint_name

An optional name for a column or table constraint. If the constraint is violated, the constraint name shows up 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 you don't specify a constraint name, the system generates one for you. Surprise! ✨

🎀 NOT NULL [ NO INHERIT ]

The column is not allowed to contain null values. Absolutely not. Zero tolerance. 🚫

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

🎀 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. Its use is discouraged in new applications. Yeah, it's giving legacy, ngl.

🎀 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. Should any row of an insert or update operation produce 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 5.5.1). 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.) Alphabetical, bestie, it's alphabetical. 🔤

🎀 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 — and 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. That's it, that's the fallback. 🍓

🎀 GENERATED ALWAYS AS ( generation_expr ) [ STORED | VIRTUAL ]

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. Main character column that only speaks when spoken to. ✨

When VIRTUAL is specified, the column will be computed when it is read, and it will not occupy any storage. When STORED is specified, the column will be computed on write and will be stored on disk. VIRTUAL is the default.

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.

⚠️ A virtual generated column cannot have a user-defined type, and the generation expression of a virtual generated column must not reference user-defined functions or types — that is, it can only use built-in functions or types. This applies also indirectly, such as for functions or types that underlie operators or casts. (This restriction does not exist for stored generated columns.) Built-ins only for the virtual girlies. 💅

🎀 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 in newly-inserted rows the column will automatically have values from the sequence assigned to it. Such a column is implicitly NOT NULL. She comes with her own sequence, it's giving self-sufficient. 👑

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.) No override for you on UPDATE, sorry bestie. 😭

The optional sequence_options clause can be used to override the parameters of the sequence. The available options include those shown for CREATE SEQUENCE (CREATE_SEQUENCE(7)), plus SEQUENCE NAME name, LOGGED, and UNLOGGED, which allow selection of the name and persistence level of the sequence. Without SEQUENCE NAME, the system chooses an unused name for the sequence. Without LOGGED or UNLOGGED, the sequence will have the same persistence level as the table. 🌈

💖 UNIQUE 💖

UNIQUE [ NULLS [ NOT ] DISTINCT ] (column constraint)
UNIQUE [ NULLS [ NOT ] DISTINCT ] ( column_name [, ... ] [, column_name
WITHOUT OVERLAPS ] ) [ INCLUDE ( column_name [, ...]) ] (table constraint)

okay so UNIQUE says: this group of one or more columns can hold only unique values, no duplicates, periodt. A unique table constraint does literally the same thing as a unique column constraint, except it gets the extra glow-up of spanning multiple columns 🫶. So the constraint is enforcing that any two rows have to differ in at least one of those columns.

Now, if WITHOUT OVERLAPS is specified for the last column, bestie, plot twist: that column gets checked for overlaps instead of equality 😳. In that case the other columns of the constraint will happily allow duplicates — as long as those duplicates don't overlap in the WITHOUT OVERLAPS column. (This is sometimes called a temporal key, if the column is a range of dates or timestamps, but PostgreSQL allows ranges over any base type. Slay.) In effect, that kind of constraint gets enforced with an EXCLUDE constraint rather than a UNIQUE constraint. So for example UNIQUE (id, valid_at WITHOUT OVERLAPS) behaves like EXCLUDE USING GIST (id WITH =, valid_at WITH &&). The WITHOUT OVERLAPS column must have a range or multirange type. Empty ranges/multiranges are not permitted 🙅‍♀️. The non-WITHOUT OVERLAPS columns of the constraint can be any type that can be compared for equality in a GiST index. By default, only range types are supported, but you can use other types by adding the btree_gist extension (which is the expected way to use this feature, iykyk).

For the purpose of a unique constraint, null values are not considered equal — unless NULLS NOT DISTINCT is specified. 👑

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. bye 👋)

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. no skipping, bestie.

Adding a unique constraint will automatically create a unique btree index on the column or group of columns used in the constraint. But if the constraint includes a WITHOUT OVERLAPS clause, it will use a GiST index instead. The created index has the same name as the unique constraint. matching names, cute 💅

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. ⚠️ so like, be careful.

👑 PRIMARY KEY 👑

PRIMARY KEY (column constraint)
PRIMARY KEY ( column_name [, ... ] [, column_name WITHOUT OVERLAPS ] ) [
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. one per table, it's giving main character energy and nobody else gets that role ✨

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. rip.)

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. so it's not just vibes, it's documented vibes 💖

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

Adding a PRIMARY KEY constraint will automatically create a unique btree index on the column or group of columns used in the constraint, or GiST if WITHOUT OVERLAPS was specified.

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. 🔥 (same warning as before, no cap)

🌈 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.

Exclusion constraints are implemented using an index that has the same name as the constraint, so each specified operator must be associated with an appropriate operator class (see Section 11.10) for the index access method index_method. Each exclude_element defines a column of the index, so it can optionally specify a collation, an operator class, operator class parameters, and/or ordering options; these are described fully under CREATE INDEX (CREATE_INDEX(7)). 📚

The access method must support amgettuple (see Chapter 63); at present this means GIN cannot be used. Although it's allowed, there is little point in using B-tree or hash indexes with an exclusion constraint, 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. it's giving GiST or nothing, bestie 💅

The predicate allows you to specify an exclusion constraint on a subset of the table; internally this creates a partial index. Note that parentheses are required around the predicate. don't forget them or it will simply not work 🙈

When establishing an exclusion 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. Additionally, those columns must be compared using the equality operator. These restrictions ensure that potentially-conflicting rows will exist in the same partition. The constraint may also refer to other columns which are not a part of any partition key, which can be compared using any appropriate operator. flexible but with rules, as always ✨

🦋 REFERENCES / FOREIGN KEY 🦋

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

If the last column is marked with PERIOD, it is treated in a special way. While the non-PERIOD columns are compared for equality (and there must be at least one of them), the PERIOD column is not. Instead, the constraint is considered satisfied if the referenced table has matching records (based on the non-PERIOD parts of the key) whose combined PERIOD values completely cover the referencing record's. In other words, the reference must have a referent for its entire duration. This column must be a range or multirange type. In addition, the referenced table must have a primary key or unique constraint declared with WITHOUT OVERLAPS. Finally, if the foreign key has a PERIOD column_name specification the corresponding refcolumn, if present, must also be marked PERIOD. If the refcolumn clause is omitted, and thus the reftable's primary key constraint chosen, the primary key must have its final column marked WITHOUT OVERLAPS. 😮‍💨 yeah, there's a lot, but it all tracks.

For each pair of referencing and referenced column, if they are of a collatable data type, then the collations must either be both deterministic or else both the same. This ensures that both columns have a consistent notion of equality. consistency is the vibe check 💅

The user must have REFERENCES permission on the referenced table (either the whole table, or the specific referenced columns). The addition of a foreign key constraint requires a SHARE ROW EXCLUSIVE lock on the referenced table. Note that foreign key constraints cannot be defined between temporary tables and permanent tables. 🚫

A value inserted into the referencing column(s) is 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; 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 is not yet implemented. 💀 yeah.

(Of course, NOT NULL constraints can be applied to the referencing column(s) to prevent these cases from arising. just saying. 😌)

In addition, when the data in the referenced columns gets changed, certain actions get 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. Same energy for ON UPDATE — it 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, then no action happens, like, at all. Referential actions are executed as part of the data changing command, even if the constraint is deferred. So here are all the possible actions for each clause, bestie:

  • NO ACTION — Produce an error if 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 if a row to be deleted or updated matches a row in the referencing table. This prevents the action even if the state after the action would not violate the foreign key constraint. In particular, it prevents updates of referenced rows to values that are distinct but compare as equal. (But it does not prevent “no-op” updates that update a column to the same value.)

In a temporal foreign key, this option is not supported.

  • 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.

In a temporal foreign key, this option is not supported.

  • SET NULL [ ( column_name [, ... ] ) ] — Set all of the referencing columns, or a specified subset of the referencing columns, to null. A subset of columns can only be specified for ON DELETE actions.

In a temporal foreign key, this option is not supported.

  • SET DEFAULT [ ( column_name [, ... ] ) ] — Set all of the referencing columns, or a specified subset of the referencing columns, to their default values. A subset of columns can only be specified for ON DELETE actions. (There must be a row in the referenced table matching the default values, if they are not null, or the operation will fail.)

In a temporal foreign key, this option is not supported.

Pro tip from me to you: 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. It's giving ✨optimization✨, no cap.

🌸 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 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. Note that deferrable constraints cannot be used as conflict arbiters in an INSERT statement that includes an ON CONFLICT clause. 💅

🦋 INITIALLY IMMEDIATE / INITIALLY DEFERRED 🦋

If a constraint is deferrable, this clause specifies the default time to check the constraint. If the constraint is INITIALLY IMMEDIATE, it is checked after each statement. This is the default. If the constraint is INITIALLY DEFERRED, it is checked only at the end of the transaction. The constraint check time can be altered with the SET CONSTRAINTS command. ✨

💜 ENFORCED / NOT ENFORCED 💜

When the constraint is ENFORCED, then the database system will ensure that the constraint is satisfied, by checking the constraint at appropriate times (after each statement or at the end of the transaction, as appropriate). That is the default. If the constraint is NOT ENFORCED, the database system will not check the constraint. It is then up to the application code to ensure that the constraints are satisfied. The database system might still assume that the data actually satisfies the constraint for optimization decisions where this does not affect the correctness of the result.

NOT ENFORCED constraints can be useful as documentation if the actual checking of the constraint at run time is too expensive.

This is currently only supported for foreign key and CHECK constraints. 🔥

🎀 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 62 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.

When creating a partition, the table access method is the access method of its partitioned table, if set.

🌈 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 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 🫶

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 66.2 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. 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)

The toast_tuple_target specifies the minimum tuple length required before we try to compress and/or move long column values into TOAST tables, and is also the target length we try to reduce the length below once toasting begins. This affects columns marked as External (for move), Main (for compression), or Extended (for both) and applies only to new tuples. There is no effect on existing rows. By default this parameter is set to allow at least 4 tuples per block, which with the default block size will be 2040 bytes. Valid values are between 128 bytes and the (block size - header), by default 8160 bytes. Changing this value may not be useful for very short or very long rows. Note that the default setting is often close to optimal, and it is possible that setting this parameter could have negative effects in some cases. This parameter cannot be set for TOAST tables. 🙈

parallel_workers (integer)

This sets the number of workers that should be used to assist a parallel scan of this table. If not set, the system will determine a value based on the relation size. The actual number of workers chosen by the planner or by utility statements that use parallel scans may be less, for example due to the setting of max_worker_processes. 🔥

  • autovacuum_enabled, toast.autovacuum_enabled (boolean) — the on/off switch for the autovacuum daemon on this specific table 🧹✨. If it's true, the autovacuum daemon will run automatic VACUUM and/or ANALYZE operations on this table, following the rules from Section 24.1.6. If it's false, this table will not be autovacuumed — except to prevent transaction ID wraparound (peep Section 24.1.5 for the wraparound-prevention lore 👀).
Heads up bestie: the autovacuum daemon does not run at all (again, except to prevent transaction ID wraparound) if the autovacuum parameter is false. Setting individual tables' storage parameters does not override that. So there is seldom much point in explicitly setting this storage parameter to true — only to false, fr fr. 💅
  • vacuum_index_cleanup, toast.vacuum_index_cleanup (enum) — forces or disables index cleanup when VACUUM runs on this table 🧼. The default value is AUTO. With OFF, index cleanup is disabled; with ON it's enabled; and with AUTO the decision is made dynamically, every single time VACUUM runs. That dynamic behavior lets VACUUM avoid needlessly scanning indexes just to remove very few dead tuples — it's giving efficiency ✨. Forcibly disabling all index cleanup can speed up VACUUM very significantly, but may also lead to severely bloated indexes if table modifications are frequent 😭. The INDEX_CLEANUP parameter of VACUUM, if specified, overrides the value of this option.
  • vacuum_truncate, toast.vacuum_truncate (boolean) — per-table value for the vacuum_truncate parameter 🎀. The TRUNCATE parameter of VACUUM, if specified, overrides the value of this option.
  • autovacuum_vacuum_threshold, toast.autovacuum_vacuum_threshold (integer) — per-table value for the autovacuum_vacuum_threshold parameter.
  • autovacuum_vacuum_max_threshold, toast.autovacuum_vacuum_max_threshold (integer) — per-table value for the autovacuum_vacuum_max_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 🍓. The special value of -1 may 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 🧊. Note that 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. Note that autovacuum will ignore per-table autovacuum_freeze_max_age parameters that are larger than the system-wide setting (it can only be set smaller) — like, smaller only, no negotiating 💀.
  • 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. Note that 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. Note that 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.
  • vacuum_max_eager_freeze_failure_rate, toast.vacuum_max_eager_freeze_failure_rate (floating point) — per-table value for the vacuum_max_eager_freeze_failure_rate parameter.
  • user_catalog_table (boolean) — declares the table as an additional catalog table for purposes of logical replication 🦋. See Section 47.6.2 for the details. This parameter cannot be set for TOAST tables, periodt. 🙈

💌 NOTES 💌

okay so the notes are short but they matter, don't skip them bestie:

  • PostgreSQL automatically creates an index for each unique constraint and primary key constraint to enforce uniqueness 👑. So basically? It is not necessary to create an index explicitly for primary key columns. (See CREATE INDEX (CREATE_INDEX(7)) for more information.)
  • Unique constraints and primary keys are not inherited in the current implementation 😭. This makes the combination of inheritance and unique constraints rather dysfunctional — it's giving cursed.
  • A table cannot have more than 1600 columns. (In practice, the effective limit is usually lower because of tuple-length constraints.) So like, 1600 is the vibe ceiling, not the practical one 💀.

✨ EXAMPLES ✨

Okay bestie, this is the fun part — actual receipts. Every single one of these is copy-pasteable and every single one slays 💅

🎬 The classics

Make a table films and a table distributors, like the origin story:

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 <> '')
);

🧊 2D array moment

Make a table with a 2-dimensional array. Yes, arrays. We contain multitudes:

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

👑 Unique table constraint

Define a unique table constraint for the table films. Unique table constraints can be defined on one or more columns of the table, no cap:

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)
);

✅ Check constraints, column edition

Define a check column constraint:

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

And now the same energy but as a check table constraint:

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

🔑 Primary key table constraint

Define a primary key table constraint for the table films. Two columns, one destiny:

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 — the first using the table constraint syntax, the second the column constraint syntax. Same vibe, different outfit 💖

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

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

🌈 Defaults, defaults, defaults

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
);

🚫 NOT NULL, twice, one with a name

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
);

💎 Unique constraints, both flavors

Define a unique constraint for the name column:

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

The same thing, but specified as a table constraint. The way that these are literally the same but the syntax is different?? Iconic:

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);

⭕ Circles that refuse to overlap

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

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

🪐 Tablespace era

Create table cinemas in tablespace diskvol1:

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

🧬 Composite type + typed table

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
);

🧩 Partitioning: the main character arc

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);

🍰 Making the actual partitions

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. Look at all these little baby partitions 🥺:

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. Nested partitioning?? She's doing the most and we respect 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. Four of them, because that's how many MODULUS 4 needs:

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 — the catch-all bestie that takes whatever's left over:

CREATE TABLE cities_partdef
    PARTITION OF cities DEFAULT;

And that's the examples, bestie. Every flag, every constraint, every partition — all accounted for 💜

💖 COMPATIBILITY 💖

okay bestie, so CREATE TABLE is basically standard SQL… but with ✨exceptions✨ and we're about to list every single one of them, no skipping, because that's just how we are. 🫶

🎀 Temporary Tables 🎀

So the syntax of CREATE TEMPORARY TABLE looks like the SQL standard's, right? But bestie, the effect is not the same. Not even close. 😭

In the standard, temp tables are defined just once and then they automatically exist (starting with empty contents, obviously) in every session that needs them. PostgreSQL said "no ma'am" and instead requires each session to issue its own CREATE TEMPORARY TABLE command for every temporary table it wants to use. The upside? Different sessions can use the same temporary table name for totally different purposes. The standard's approach forces all instances of a given temporary table name to have the same table structure, which is giving… restrictive. 💅

Lowkey the standard's definition of temp table behavior is widely ignored anyway. PostgreSQL's behavior here is similar to several other SQL databases, so it's giving "everyone's doing it, it's fine." 🦋

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. But since PostgreSQL doesn't support SQL modules at all, that distinction is simply not relevant here. Periodt. ✨

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

⚠️ Use of these keywords is discouraged, since future versions of PostgreSQL might adopt a more standard-compliant interpretation of their meaning. So like… don't get attached. 🙈

The ON COMMIT clause for temporary tables also resembles the SQL standard, but with 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. (different!! 😤)
  • The ON COMMIT DROP option does not exist in SQL. It's a PostgreSQL thing.

💅 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 uniqueness should only be enforced at the end of the statement. This matters 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. She's correct, but she's slow. That's the tradeoff, bestie.

🧚 Column Check Constraints 🧚

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

⭐ EXCLUDE Constraint ⭐

The EXCLUDE constraint type is a PostgreSQL extension. That's it, that's the whole note. Iconic brevity. 💖

🦋 Foreign Key Constraints 🦋

Two things are PostgreSQL extensions here, bestie:

  • The ability to specify column lists in the foreign key actions SET DEFAULT and SET NULL.
  • 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, it's giving imposter) is a PostgreSQL extension to the SQL standard that's included for compatibility with some other database systems — and for symmetry with the NOT NULL constraint, because aesthetics matter. ✨

Since it's the default for any column anyway, its presence is simply noise. Like saying "no cap" after every sentence. We know. 😭

💜 Constraint Naming 💜

The SQL standard says table and domain constraints must have names that are unique across the schema containing the table or domain. PostgreSQL is laxer, bestie: it only requires constraint names to be unique across the constraints attached to a particular table or domain. Chill vibes. 🌈

However — and this is the catch — that extra freedom does not exist for index-based constraints (UNIQUE, PRIMARY KEY, and EXCLUDE constraints). Why? Because the associated index is named the same as the constraint, and index names must be unique across all relations within the same schema. The rules said "be free" and the indexes said "actually no." 🙈

🌸 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. We're on our own path, main character energy only. 👑

🍓 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 aren't in themselves very useful, but disallowing them creates odd special cases for ALTER TABLE DROP COLUMN, so it seems cleaner to just ignore this spec restriction. Honestly? Valid reasoning. 💅

🧚 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. Like, it works, but it's giving "we didn't plan for this." 😭

✨ Generated Columns ✨

The options STORED and VIRTUAL are not standard, but they are used by other SQL implementations too, so it's a whole vibe. The SQL standard does not specify the storage of generated columns. Make of that what you will. 💖

🌈 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. It's a mix-and-match situation, bestie. Some in, some out, we move. 💅

⭐ WITH Clause ⭐

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

💖 Tablespaces 💖

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

🦋 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. So… subset. Noted. 🌸

🎀 PARTITION BY Clause 🎀

The PARTITION BY clause is a PostgreSQL extension. Periodt. 💅

🎀 PARTITION OF Clause 🎀

The PARTITION OF clause is a PostgreSQL extension. Matching set, as she should. ✨

👑 SEE ALSO 👑

go read these next, bestie, they're all in the same friend group:

and that's a wrap on CREATE TABLE(7)!! 🎀✨ this page is from PostgreSQL 18.6, dated 2026 — yes bestie, 2026, she's from the future and she ate. 💅 go make some tables, you absolute icon. 🫶💖

📦 where this page comes from