CREATE_TABLE(7pg16)

📦 version 16.15, in opensuse-leap 16.0

CREATE TABLE — that's CREATE_TABLE(7pg16) from the PostgreSQL 16.15 docs, bestie 💖 this is part 1, and we're keeping every tiny detail. no skips. no cap. ✨

🌸 NAME 🌸

CREATE_TABLE — define a new table. that's literally the whole job: she defines a new table, and you're the main character making it happen 💅.

🌈 SYNOPSIS 🌈

okay, here's the whole syntax situation — do not let the wall of text scare you, it's just every flavor of CREATE TABLE lined up like outfits 🎀:

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 |
  NULL |
  CHECK ( expression ) [ NO INHERIT ] |
  DEFAULT default_expr |
  GENERATED ALWAYS AS ( generation_expr ) STORED |
  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 ]

and table_constraint is:

[ CONSTRAINT constraint_name ]
{ CHECK ( expression ) [ NO INHERIT ] |
  UNIQUE [ NULLS [ NOT ] DISTINCT ] ( 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 | 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 ✨

CREATE TABLE makes a brand-new, initially empty table in the current database — think blank canvas but make it relational 🎨. The table is owned by the user who issues the command, so yes, you're the main character here 👑.

If you give a schema name (like CREATE TABLE myschema.mytable ...), the table gets created in that schema. If you don't, it goes in the current schema. Temporary tables live in a special schema, so you cannot give a schema name when you're creating a temporary table — that's just the rule, bestie 🫶. The table name has to be distinct from the name of any other relation in the same schema — and by relation we mean table, sequence, index, view, materialized view, or foreign table. all of those count.

Also, CREATE TABLE automatically creates a data type that represents the composite type corresponding to one row of the table. Because of that, tables cannot have the same name as any existing data type in the same schema. so don't try to twin with a type, it's not that kind of party 💀.

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 — very "boundaries are self-care" of it 🌸.

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.

To be able to create a table, you must have USAGE privilege on all column types or the type in the OF clause, respectively. permissions check, bestie — no vibes-only table creation 🔐.

🧚 PARAMETERS 🧚

okay, this is the big one. every parameter, every caveat, every little "actually" — we're doing it 💅

🧊 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). The default search_path includes the temporary schema first, and so identically named existing permanent tables are not chosen for new plans 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 30), 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.

🎀 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. so like, it might be a totally different situation under the same name, bestie 🙈.

🏷️ table_name 🏷️

The name (optionally schema-qualified) of the table to be created. simple, iconic, necessary 💅.

🧬 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.

🗄️ STORAGE { PLAIN | EXTERNAL | EXTENDED | MAIN | DEFAULT } 🗄️

This form sets the storage mode for the column. This 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 is inline, uncompressed. MAIN is for inline, compressible data. EXTERNAL is for external, uncompressed data, and 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 73.2 for more information.

🗜️ COMPRESSION compression_method 🗜️

The COMPRESSION clause sets the compression method for the column. Compression is supported only for variable-width data types, and is used only when the column's storage mode is main or extended. (See ALTER TABLE (ALTER_TABLE(7)) for information on column storage modes.) Setting this property for a partitioned table has no direct effect, because such tables have no storage of their own, but the configured value will be inherited by newly-created partitions. The supported compression methods are pglz and lz4. (lz4 is available only if --with-lz4 was used when building PostgreSQL.) In addition, 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.

part 2 has the rest of the parameters, bestie — same chaotic energy, same zero-skip policy 🌈

💫 INHERITS ( parent_table [, ... ] ) 💫

Okay so this optional INHERITS clause — bestie listen — it lets you pass a list of tables and your shiny new table automatically inherits all their columns. And the parents? They can be plain tables or foreign tables. Versatile icons only 💅.

Using INHERITS creates a persistent relationship between the new child table and its parent table(s). Schema modifications to the parent(s) normally propagate down to the children too, and by default the child table's data gets included when you scan the parent(s). It's giving family tree, fr fr 🧚.

Now for the messy part 😭 — if the same column name shows up in more than one parent table, you get an error unless the data types match in every one of those parent tables. If there's no conflict, the duplicate columns get merged into a single column in the new table. And if your new table's column name list contains a name that's also inherited, the data type must match the inherited column(s) too, and the definitions merge into one. If the new table explicitly specifies a default value for the column, that default overrides any defaults from the inherited declarations. Otherwise, any parents specifying defaults for that column must all specify the same default, or boom — error reported 💀.

CHECK constraints merge in basically the same way as columns: if multiple parent tables and/or the new table definition contain identically-named CHECK constraints, they must all have the same check expression, or error. Constraints with the same name and expression merge into one copy. A constraint marked NO INHERIT in a parent will not be considered, periodt. Also note — an unnamed CHECK constraint in the new table will never be merged, because a unique name always gets chosen for it. Not me being picky, that's just how it is 🙈.

Column STORAGE settings get copied from parent tables too. Freebies ✨.

And one lil caveat (iykyk): if a column in the parent table is an identity column, that property is not inherited. But a column in the child table can absolutely be declared an identity column if you want to. Main character energy 👑.

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

The optional PARTITION BY clause specifies the strategy for partitioning the table, and the table you just made is now called a partitioned table. The parenthesized list of columns or expressions forms the partition key for the table. When you're doing range or hash partitioning, the partition key can include multiple columns or expressions — up to 32, but that limit can be altered when building PostgreSQL. For list partitioning though? The partition key has to be a single column or expression. No exceptions, bestie 🎀.

Range and list partitioning need a btree operator class, while hash partitioning needs a hash operator class. If you don't specify an operator class explicitly, the default operator class of the appropriate type gets used — and if no default operator class exists, an error gets raised. When you're using hash partitioning, the operator class you use must implement support function 2 (see Section 38.16.3 for the details, go look 👀).

So a partitioned table gets divided into sub-tables (called partitions) which you create with separate CREATE TABLE commands. The partitioned table itself is empty. A data row you insert gets routed to a partition based on the value of the columns or expressions in the partition key. And if no existing partition matches the values in the new row? Error reported 😭.

Partitioned tables do not support EXCLUDE constraints — but you can define these constraints on the individual partitions. Workaround slay 💅.

See Section 5.11 for more discussion on table partitioning, if you're curious 🦋.

🦋 PARTITION OF parent_table { FOR VALUES partition_bound_spec | DEFAULT } 🦋

This creates the table as a partition of the specified parent table. You can create it 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 already exist in the parent table get cloned onto the new partition. Copy-paste but make it fashion ✨.

The partition_bound_spec must correspond to the partitioning method and partition key of the parent table, and it must not overlap with any existing partition of that parent. The form with IN is for list partitioning, the form with FROM and TO is for range partitioning, and the form with WITH is for hash partitioning. Match the vibe to the method, okay? 🫶

partition_bound_expr is any variable-free expression — so 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 gets evaluated once at table creation time, so it can even contain volatile expressions like CURRENT_TIMESTAMP. Iconic and slightly chaotic 💀.

When you're creating a list partition, NULL can be specified to signify that the partition allows the partition key column to be null. However — there can't be more than one such list partition for a given parent table. And NULL cannot be specified for range partitions. Rules are rules 🌸.

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 means the values in the FROM list are valid values of the corresponding partition key columns for this partition, while those in the TO list are not. And ngl you gotta read this statement 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. Got it? Got it 💖.

The special values MINVALUE and MAXVALUE may be used when creating a range partition to indicate that there's 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. Unbounded queen behavior 👑.

When you're 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. Like, 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". Chef's kiss 🍓.

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 clever 💀.

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 ways of saying 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". So the range FROM ('infinity') TO (MAXVALUE) is not an empty range — it allows precisely one value to be stored: "infinity". Mind blown, I know 😭✨.

If DEFAULT is specified, the table gets created as the default partition of the parent table. This option is not available for hash-partitioned tables, sorry bestie 🙈. A partition key value that doesn't fit into any other partition of the given parent gets routed to the default partition. Catch-all energy 🎀.

Now — when a table already has an existing DEFAULT partition and you add a new partition to it, the default partition must be scanned to verify it doesn't contain any rows that properly belong in the new partition. If the default partition has a large number of rows, this may be slow 🐌. The scan gets skipped if the default partition is a foreign table, or if it has a constraint which proves it cannot contain rows that should be placed in the new partition. Convenient ✨.

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 you're 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 the examples, below 👀). However — it's 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 lets you increase the number of partitions incrementally without needing to move all the data at once. Slay for scalability 💅.

For example: suppose you have a hash-partitioned table with 8 partitions, each of which has modulus 8, but then you 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's still better than having to create a whole new table and move all the data at once. Genuinely a glow-up 🌈.

A partition must have the same column names and types as the partitioned table it belongs to. Modifications to the column names or types of a partitioned table automatically propagate to all partitions. CHECK constraints get inherited automatically by every partition, but an individual partition may specify additional CHECK constraints — and additional constraints with the same name and condition as the one in the parent get 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. Sneaky detail, but important 😤.

Rows inserted into a partitioned table get automatically routed to the correct partition. And if no suitable partition exists? Error occurs. Simple as that 🦋.

okay so bestie, quick vibe check on operations that normally hit a table and all of its inheritance children — stuff like TRUNCATE — they’ll cascade to all partitions too, no cap. But they may also be performed on an individual partition.

note note note: creating a partition with PARTITION OF means taking an ACCESS EXCLUSIVE lock on the parent partitioned table. same energy for dropping a partition with DROP TABLE — that requires an ACCESS EXCLUSIVE lock on the parent table, periodt. you can use ALTER TABLE ATTACH/DETACH PARTITION to do these operations with a weaker lock, which lowkey reduces interference with concurrent operations on the partitioned table. slay.

🦋 LIKE source_table [ like_option ... ]

for real, the LIKE clause specifies a source_table from which the new table automatically copies all column names, their data types, and their not-null constraints. 💅

unlike INHERITS, the new table and the 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. iykyk.

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. no merging, no drama.

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, check constraints, indexes, and extended statistics will be copied. the default behavior is to exclude comments, resulting in the corresponding objects in the new table having no comments.
  • INCLUDING COMPRESSION — compression method of the columns will be copied. the default behavior is to exclude compression methods, resulting in columns having 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.
  • INCLUDING DEFAULTS — default expressions for the copied column definitions will be copied. otherwise, default expressions are not copied, resulting in the copied columns in the new table having 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.
  • INCLUDING GENERATED — any generation expressions 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.
  • 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 will be copied. the default behavior is to exclude STORAGE settings, resulting in the copied columns in the new table having type-specific default settings. for more on STORAGE settings, see Section 73.2.
  • 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 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. cute.

🎀 CONSTRAINT constraint_name

this gives 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. iconic.

💖 NOT NULL

the column is not allowed to contain null values. simple as that.

🌸 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. bestie, don’t make it your main character.

⭐ 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 5.4.1). 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. rules are rules.

👑 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.

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 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 [ NULLS [ NOT ] DISTINCT ] (column constraint)

🌈 UNIQUE [ NULLS [ NOT ] DISTINCT ] ( column_name [, ... ] ) [ INCLUDE ( column_name [, ...]) ] (table constraint)

UNIQUE [ NULLS [ NOT ] DISTINCT ] (column constraint)
UNIQUE [ NULLS [ NOT ] DISTINCT ] ( 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, 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.)

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. periodt. 💜

…and bestie, that optional INCLUDE clause? It's doing the absolute most by doing the least 💅 It adds one or more columns to that index that are pure payload — like, uniqueness is not enforced on them, and the index can't even be searched on the basis of those columns. So what are they even for? An index-only scan, babe. That's the vibe. But — and this is the important part — even though the constraint isn't enforced on the included columns, it still depends on them. Which means some operations on those columns (e.g., DROP COLUMN) can cause cascaded constraint and index deletion. So don't come for those columns unless you're ready for the whole friend group to leave with them 😭

👑 PRIMARY KEY (column constraint)

PRIMARY KEY ( column_name [, ... ] ) [ INCLUDE ( column_name [, ...]) ]

👑 PRIMARY KEY (table constraint)

The PRIMARY KEY constraint says: this column (or these columns) can only hold unique (non-duplicate) nonnull values. And listen — only one primary key per table, periodt. Whether you write it as a column constraint or a table constraint, it's one. That's the rule 🔥

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

PRIMARY KEY enforces the exact same data constraints as a combo of UNIQUE and NOT NULL. But identifying a set of columns as the primary key also gives you metadata about the design of the schema, because a primary key implies that other tables can rely on this set of columns as a unique identifier for rows. It's giving main character energy for your 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. Free index, no cap ✨

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. (Yes, same warning twice. It's that serious 🙈)

🚫 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. But exclusion constraints can specify constraints that are way 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. Cute, right? 🦋 The operator(s) are required to be commutative.

Exclusion constraints are implemented using an index, 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 64); 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. Slay 💅

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, bestie, it will not work and you will be sad 😭

🔗 REFERENCES (column constraint)

REFERENCES reftable [ ( refcolumn ) ] [ MATCH matchtype ] [ ON DELETE
referential_action ] [ ON UPDATE referential_action ]

🔗 FOREIGN KEY (table constraint)

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

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). 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. That's just not a thing, sorry 🫶

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 👑). Here's the tea:

  • 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 💀

(Of course, NOT NULL constraints can be applied to the referencing column(s) to prevent these cases from arising. You have options, bestie ✨)

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 specifies the action to perform when a referenced row in the referenced table is being deleted. Likewise, the ON UPDATE clause specifies the action to perform 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. 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. It's giving chain reaction 🌀
  • 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.
  • 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. No row, no vibe 😭)

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 performance glow-up, we love to see it 💖

⏳ 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. That's the catch, bestie 🙈

🕐 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. You're the main character, you decide when ⭐

🛠️ 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 63 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. Old syntax, still valid, we respect the elders 🫡

🎬 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. Do nothing, beautifully ✨

DELETE ROWS

Every single row in the temp table gets yeeted at the end of each transaction block — like, it's basically an automatic TRUNCATE happening at every commit. Iconic but ruthless. And heads up bestie: when you use this on a partitioned table, it does not cascade down to its partitions. 💅

DROP

The temp table itself gets dropped at the end of the current transaction block. 🫶 When you use it on a partitioned table, this action drops its partitions too, and when used on tables with inheritance children, it drops the dependent children. Like, the whole family tree, gone.

TABLESPACE tablespace_name

So tablespace_name is literally just the name of the tablespace where the new table is gonna live. 🏠 If you don't specify one, default_tablespace gets consulted — or temp_tablespaces if the table is temporary. Easy.

For partitioned tables though? Since no storage is required for the table itself, the tablespace you specify here overrides default_tablespace as the default tablespace to use for any newly created partitions when no other tablespace is explicitly specified. That's the plot twist. ✨

USING INDEX TABLESPACE tablespace_name

This clause lets you pick the tablespace where the index associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint gets created. 🎀 If you don't specify it, default_tablespace gets consulted — or temp_tablespaces if the table is temporary.

✨ Storage Parameters ✨

Okay so the WITH clause can specify storage parameters for tables, and also for indexes associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint. Storage parameters for indexes are documented over in CREATE INDEX (CREATE_INDEX(7)) — go look if you're nosy. 👀

The storage parameters currently available for tables are listed below. For many of these parameters, as shown, there's 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 73.2 for more info about TOAST, iykyk). If a table parameter value is set and the equivalent toast. parameter is not, the TOAST table will just use the table's parameter value. 🍞

Big caveat bestie: 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 you specify a smaller fillfactor, INSERT operations pack table pages only to the indicated percentage — the remaining space on each page is reserved for updating rows on that page. 🎯

That gives UPDATE a chance to place the updated copy of a row on the same page as the original, which is way 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. Match the vibe to the workload.

This parameter cannot be set for TOAST tables. 🙈

toast_tuple_target (integer)

toast_tuple_target specifies the minimum tuple length required before we try to compress and/or move long column values into TOAST tables, and it's 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 — periodt.

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.

Real talk: the default setting is often close to optimal, and it's 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 it's 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. So like, it's a vibe request, not a guarantee. 💅

autovacuum_enabled, toast.autovacuum_enabled (boolean)

Enables or disables the autovacuum daemon for a particular table. 🧹 If true, the autovacuum daemon will perform automatic VACUUM and/or ANALYZE operations on this table following the rules discussed in Section 25.1.6. If false, this table will not be autovacuumed — except to prevent transaction ID wraparound. See Section 25.1.5 for more about wraparound prevention.

Note that the autovacuum daemon does not run at all (except to prevent transaction ID wraparound) if the autovacuum parameter is false; setting individual tables' storage parameters does not override that. So there's seldom much point in explicitly setting this storage parameter to true — only to false. 🤷‍♀️

vacuum_index_cleanup, toast.vacuum_index_cleanup (enum)

Forces or disables index cleanup when VACUUM is run on this table. The default value is AUTO. With OFF, index cleanup is disabled, with ON it is enabled, and with AUTO a decision is made dynamically, each time VACUUM runs. 🎲

That dynamic behavior lets VACUUM avoid needlessly scanning indexes just to remove very few dead tuples.

Careful: 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)

Enables or disables vacuum trying to truncate off any empty pages at the end of this table. The default value is true. ✂️ If true, VACUUM and autovacuum do the truncation and the disk space for the truncated pages is returned to the operating system.

Note that the truncation requires an ACCESS EXCLUSIVE lock on the table — so, you know, plan around that.

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_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). 📉

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. 🪵

user_catalog_table (boolean)

Declare the table as an additional catalog table for purposes of logical replication. See Section 49.6.2 for details. This parameter cannot be set for TOAST tables. 🙈

📝 NOTES

PostgreSQL automatically creates an index for each unique constraint and primary key constraint to enforce uniqueness. So like, you do not need to create an index explicitly for primary key columns. It's giving free real estate. (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. 😭 Not the inheritance drama.

A table cannot have more than 1600 columns. (In practice, the effective limit is usually lower because of tuple-length constraints.) 💀

✨ EXAMPLES ✨

Okay bestie, this is the part where it all comes together — every single example, served fresh, no skips. Let's go 🎀

💖 The classic starting point

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 <> '')
);

Two tables, one shot, iconic behavior honestly 👑

🦋 Arrays, yes we can

Create a table with a 2-dimensional array:

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

int[][] — two whole dimensions just vibing in a column. we love a multidimensional moment ✨

🌸 Unique table constraint energy

Define a unique table constraint for the table films. Unique table constraints can be defined on one or more columns of the table:

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)
);

notice the CONSTRAINT production naming — she has a name, she's the main character 💅

🐚 Check yourself (column edition)

Define a check column constraint:

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

did > 100 — the column is literally gatekeeping. periodt.

🎀 Check yourself (table edition)

Define a check table constraint:

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

now the whole table's in on it, con1 said no empty names and no small dids 🫶

⭐ Primary key, but make it a table constraint

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)
);

two columns, one primary key, code_title doing the absolute most and honestly? slay 🔥

🧚 Two ways, same vibe

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:

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

both fr fr the same thing — pick whichever syntax you find cuter 😌

💜 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
);

three separate default vibes in one table: a literal 'Luso Films', a nextval('distributors_serial') pull, and current_timestamp for insert time. chef's kiss 🍓

🌈 NOT NULL, but named

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
);

one of them got a whole government name (no_null) and the other is just out here unnamed. both valid 💖

🎀 Unique, column style

Define a unique constraint for the name column:

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

short, sweet, unique ✨

🫶 Unique, table-constraint style

The same, specified as a table constraint:

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

same result, different outfit. iykyk 💅

🔥 Fillfactor flex

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);

70 in two places — once on the unique index, once on the table itself. consistency queen 👑

💀 Exclusion constraints, the coolest ones

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

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

EXCLUDE USING gist (c WITH &&) — literally no overlapping circles allowed. geometry said nope 🙈

🌸 Tablespace placement

Create table cinemas in tablespace diskvol1:

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

TABLESPACE diskvol1 — she's moved in, she lives there now 🦋

🧚 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
);

OF employee_type — the table is literally built from a type. and salary WITH OPTIONS DEFAULT 1000 is how you sneak a default onto a typed column 💖

⭐ Range partitioning, entry level

Create a range partitioned table:

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

PARTITION BY RANGE (logdate) — the beginning of a whole partitioning saga, buckle up 🌈

🎀 Range partitioning with multiple columns

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));

the partition key is (EXTRACT(YEAR FROM logdate), EXTRACT(MONTH FROM logdate)) — two expressions, one key. highkey obsessed 🔥

🐚 List partitioning

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));

PARTITION BY LIST (left(lower(name), 1)) — grouping cities by their first letter, lowercase, obviously 💅

💜 Hash partitioning

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);

PARTITION BY HASH (order_id) — no peeking at ranges or lists, we're hashing now 🫶

🌸 Making a partition of a range table

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');

PARTITION OF measurement + FOR VALUES FROM ('2016-07-01') TO ('2016-08-01') — that's the whole recipe 🎀

⭐ Multi-column range partitions, in bulk

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);

look at those tuples — (MINVALUE, MINVALUE), (2016, 11), (2016, 12), (2017, 01) — all lined up like little shelves 🦋

🧚 List partition with a check

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');

FOR VALUES IN ('a', 'b') and a bonus CONSTRAINT city_id_nonzero CHECK (city_id != 0). overachiever 💖

🔥 A partition that's also a partitioned table

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);

partition-ception — cities_ab is a partition and gets its own PARTITION BY RANGE (population), then cities_ab_10000_to_100000 shows up as its kid 😭 so good

💜 Hash partitions, the whole set

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);

MODULUS 4 with REMAINDER 0 through REMAINDER 3 — all four accounted for, no leftovers, no crumbs 🌈

🍓 The default partition

Create a default partition:

CREATE TABLE cities_partdef
    PARTITION OF cities DEFAULT;

one word: DEFAULT. the catch-all, the safety net, the "everything else goes here" icon 💅

and that's the examples, bestie — every last one of them, untouched and accounted for 🫶 (more to come, hold tight 💖)

💖 COMPATIBILITY 💖

okay bestie, so CREATE TABLE does conform to the SQL standard… mostly. but there's a whole little list of exceptions and honestly? some of them are iconic. let's get into it ✨

🌸 Temporary Tables

so the syntax of CREATE TEMPORARY TABLE looks like the SQL standard's, but the effect is not the same, bestie. in the standard, temporary tables are defined just once and then automatically exist (starting out empty) in every session that needs them. cute, right?

PostgreSQL is not about that life. instead, each session has to issue its own CREATE TEMPORARY TABLE command for every temporary table it's gonna use. sounds extra, but it actually slaps: it lets different sessions use the same temporary table name for totally different purposes. the standard's approach would force every instance of a given temporary-table name to have the exact same structure. 🙈

the standard's definition of temporary-table behavior is, like, widely ignored anyway. PostgreSQL's vibe here is similar to several other SQL databases. 💅

also: the SQL standard distinguishes between global and local temporary tables, where a local one has a separate set of contents for each SQL module within each session — though its definition is still shared across sessions. but PostgreSQL doesn't support SQL modules, so this whole distinction is not relevant here. moving on 🎀

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, because future versions of PostgreSQL might adopt a more standard-compliant interpretation of what they mean. so like, don't get attached 😭

the ON COMMIT clause for temporary tables also resembles the standard, but there are differences:

  • if ON COMMIT is omitted, SQL says the default is ON COMMIT DELETE ROWS. but PostgreSQL's default is ON COMMIT PRESERVE ROWS. plot twist 🌈
  • the ON COMMIT DROP option does not exist in SQL at all.

💜 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 — and that difference shows up when, for example, a single command updates multiple key values. 👑

to get standard-compliant behavior, declare the constraint as DEFERRABLE but not deferred (i.e., INITIALLY IMMEDIATE). but heads up:

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

🦋 Column Check Constraints

the SQL standard says 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 exactly alike. we're chill like that ✨

🎀 EXCLUDE Constraint

the EXCLUDE constraint type is a PostgreSQL extension. periodt.

🍓 Foreign Key Constraints

two extension moments here:

  • being able to specify column lists in the foreign key actions SET DEFAULT and SET NULL is a PostgreSQL extension.
  • it's also 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” (which is actually a non-constraint, ngl) is a PostgreSQL extension to the SQL standard. it's included for compatibility with some other database systems (and for symmetry with the NOT NULL constraint). and since it's the default for any column anyway… its presence is simply noise. 🙈

⭐ 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 💅 — it only requires constraint names to be unique across the constraints attached to a particular table or domain.

but! that 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. rules are rules 🎀

currently, PostgreSQL doesn't record names for NOT NULL constraints at all, so they're not subject to the uniqueness restriction. this might change in a future release, so don't build your whole personality on it 🌸

🔥 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. iykyk 😭

👑 Zero-Column Tables

PostgreSQL allows you to create a table with no columns at all — for example:

CREATE TABLE foo();

this is an extension from the SQL standard, which does not allow zero-column tables. are zero-column tables useful on their own? literally not really. but disallowing them creates odd special cases for ALTER TABLE DROP COLUMN, so it seems cleaner to just ignore this spec restriction. big brain energy 🧠✨

🌈 Multiple Identity Columns

PostgreSQL lets a table have more than one identity column. the standard specifies a table can have at most one identity column. this is relaxed mainly to give more flexibility for doing schema changes or migrations.

but lowkey important:

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. we're just out here pioneering 🫶

💜 LIKE Clause

while a LIKE clause exists in the SQL standard, many of the options PostgreSQL accepts for it are not in the standard, and some of the standard's options are not implemented by PostgreSQL. it's giving mutual misunderstanding 💅

🎀 WITH Clause

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

🦋 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 plus 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 👑

go read these next, bestie, they're all linked:

🌸 okay that's the whole page, you made it!! this was PostgreSQL 16.15, dated 2026, and it's the CREATE TABLE(7) page — go build something iconic with it, ily, bye bestie 🫶💖✨

📦 where this page comes from