CREATE_TABLE(7pg15)

CREATE TABLE time, bestie! This is the PostgreSQL 15.19 Documentation page CREATE_TABLE(7pg15) — the whole “define a new table” situation. Grab a strawberry drink 🍓 and let’s build something iconic. 💅

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🌸 NAME 🌸

CREATE_TABLE — define a new table. That’s it, that’s the mission. New table, fresh start, main character energy. 👑

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✨ SYNOPSIS ✨

Okay bestie, here’s the full grammar in all its glory — no shortcuts, no cuties, every line exactly as it belongs:

CREATE [ [ GLOBAL | LOCAL ] { TEMPORARY | TEMP } | UNLOGGED ] TABLE [ IF NOT EXISTS ] table_name ( [
  { column_name data_type [ 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 [, ... ] ) ] }

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💅 DESCRIPTION 💅

Okay so CREATE TABLE will create a new, initially empty table in the current database. The table will be owned by the user issuing the command. Slay. 👑

If a schema name is given (for example, CREATE TABLE myschema.mytable ...) then the table is created in the specified schema. Otherwise it is created in the current schema. Temporary tables exist in a special schema, so a schema name cannot be given when creating a temporary table. The name of the table must be distinct from the name of any other relation (table, sequence, index, view, materialized view, or foreign table) in the same schema. No name collisions, bestie — that’s the vibe check. 🚫

CREATE TABLE also automatically creates a data type that represents the composite type corresponding to one row of the table. Therefore, tables cannot have the same name as any existing data type in the same schema. The table and the type are lowkey linked like that. 🫶

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. Think of them as the rules of the group chat. ✨

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. Cute and functional. 🎀

To be able to create a table, you must have USAGE privilege on all column types or the type in the OF clause, respectively. Permission check first, table second. 🔑

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🎀 PARAMETERS 🎀

💖 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. Temporary means temporary, bestie — it’s giving fleeting. 🦋

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. Not me reminding you to ANALYZE — but yes, actually me. 😭

Optionally, GLOBAL or LOCAL can be written before TEMPORARY or TEMP. This presently makes no difference in PostgreSQL and is deprecated; see Compatibility below. Deprecated, bestie — cute historical vibes, but don’t rely on it.

🌈 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. Speed? Yes. But…

Important caveat: 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. Not me warning you that the data can ghost you after a crash. 💀

If this is specified, any sequences created together with the unlogged table (for identity or serial columns) are also created as unlogged. Matching energy, matching unlogged status. ✨

🦋 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 won’t yell at you, but it also won’t promise the existing table is your aesthetic. 🙈

🍓 table_name 🍓

The name (optionally schema-qualified) of the table to be created. Name it something iconic. 💅

👑 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). Attachment issues, but make it database. 😭

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. So the type is the blueprint, and CREATE TABLE gets to add the cute details. 🎀

🌸 column_name 🌸

The name of a column to be created in the new table. Every column deserves a name, bestie. 🫶

💜 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. Type check: passed. ✅

✨ 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. Collation girlies, rise. 🌸

🔥 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. Compression: understood, inherited, and very much a vibe. 🧚

🎀 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. Family tree, but make it SQL. 🌈

Use of INHERITS creates a persistent relationship between the new child table and its parent table(s). Schema modifications to the parent(s) normally propagate to children as well, and by default the data of the child table is included in scans of the parent(s). The child is literally in the parent’s scans — that’s the relationship. 💖

Okay so bestie, if the same column name shows up in more than one parent table, Postgres will literally throw an error unless the data types of those columns match in each parent table. If there’s no conflict, the duplicate columns get merged into one single column in the new table. And if the new table’s column name list contains a name that’s also inherited, the data type has to match the inherited column(s) too, and the definitions get merged into one. If the new table explicitly sets a default value for that column, that default overrides any inherited defaults. Otherwise, every parent that specifies a default for the column has to specify the same default, or boom — error reported. 💅

CHECK constraints merge in basically the same way: if multiple parent tables and/or the new table definition contain identically-named CHECK constraints, they all have to have the same check expression, or an error gets reported. Constraints with the same name and expression get merged into one copy. A constraint marked NO INHERIT in a parent will not be considered. And notice: an unnamed CHECK constraint in the new table will never be merged, because a unique name will always be chosen for it. No cap. ✨

Column STORAGE settings are also copied from parent tables. And 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 you want. 🫶

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💖 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) — but for list partitioning, the partition key must consist of a single column or expression. Periodt. 🌈

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 38.16.3 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. It’s giving “you had one job” energy, but that’s the rule. 💀

Partitioned tables do not support EXCLUDE constraints; however, you can define these constraints on individual partitions. See Section 5.11 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. Slay, inheritance but make it partitions. 👑

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. Iconic, honestly. 💜

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

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

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). Not me making that mistake in front of the whole group chat. 🙈

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". Literally one. 💅

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

When a table has an existing DEFAULT partition and a new partition is added to it, the default partition must be scanned to verify that it does not contain any rows which properly belong in the new partition. If the default partition contains a large number of rows, this may be slow. The scan will be skipped if the default partition is a foreign table or if it has a constraint which proves that it cannot contain rows which should be placed in the new partition. Lowkey a vibe check for your rows. 🔍

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, honestly. ✨

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

Rows inserted into a partitioned table will be automatically routed to the correct partition. If no suitable partition exists, an error will occur. Operations such as TRUNCATE which normally affect a table and all of its inheritance children will cascade to all partitions, but may also be performed on an individual partition. Main character table behavior, fr fr. 👑

• quick heads-up bestie: making a partition with PARTITION OF means you gotta grab an ACCESS EXCLUSIVE lock on the parent partitioned table. Same deal when you drop a partition with DROP TABLE — ACCESS EXCLUSIVE lock on the parent table, no cap. the glow-up move is to use ALTER TABLE ATTACH/DETACH PARTITION instead, which does the same thing with a weaker lock, so you're not out here blocking everyone else's concurrent operations on the partitioned table. 💅
• LIKE source_table [ like_option ... ] — this clause says "copy that table's fit," like literally: the new table automatically copies all column names, their data types, and their not-null constraints. ✨

But — and this is the key difference from INHERITS — the new table and the original table are completely decoupled once creation finishes. Changes to the original don't flow to the new one, and you can't sneak the new table's data into scans of the original. Not a thing. 🙅‍♀️

Also unlike INHERITS, columns and constraints copied by LIKE do not get merged with similarly named columns and constraints. If the same name shows up explicitly or in another LIKE clause, that's an error, bestie. 💀

The optional like_option clauses pick which extra properties of the original table get copied. Say INCLUDING and you copy it, say EXCLUDING and you skip it. Default is EXCLUDING. If you spec the same kind of object multiple times, the last one wins. The options are:

• INCLUDING COMMENTS — comments for the copied columns, check constraints, indexes, and extended statistics get copied. Default behavior excludes comments, so the matching objects in the new table just have no comments. 🫥
• INCLUDING COMPRESSION — the compression method of the columns gets copied. Default excludes compression methods, so columns get the default compression method.
• INCLUDING CONSTRAINTS — CHECK constraints get copied. No distinction between column constraints and table constraints, they're all just constraints. Not-null constraints are always copied to the new table regardless.
• INCLUDING DEFAULTS — default expressions for the copied column definitions get copied. Otherwise defaults aren't copied and the copied columns in the new table have null defaults. fair warning tho: copying defaults that call database-modification functions, like nextval, can create a functional linkage between the original and new tables. 😬
• INCLUDING GENERATED — any generation expressions of copied column definitions get copied. By default, new columns are regular base columns.
• INCLUDING IDENTITY — any identity specifications of copied column definitions get 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 get created on the new table too. Names for the new indexes and constraints are chosen by the default rules, no matter how the originals were named (this behavior avoids possible duplicate-name failures for the new indexes — iconic problem-solving honestly).
• INCLUDING STATISTICS — extended statistics get copied to the new table. 📊
• INCLUDING STORAGE — STORAGE settings for the copied column definitions get copied. Default excludes STORAGE settings, so the copied columns in the new table get type-specific default settings. For more on STORAGE settings, see Section 73.2.
• INCLUDING ALL — INCLUDING ALL is the abbreviated form that selects all the available individual options. (Handy trick: write individual EXCLUDING clauses after INCLUDING ALL to get everything but a few specific options. iykyk 💫)

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

• CONSTRAINT constraint_name — an optional name for a column or table constraint. Why care? Because if the constraint is violated, the constraint name shows up in the error messages — so names like col must be positive can communicate helpful constraint info straight to client applications. (You need double-quotes to specify constraint names that contain spaces.) If you don't name it, the system generates a name for you. 🏷️
• 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 exists only for compatibility with non-standard SQL databases, and its use is discouraged in new applications. don't do it, bestie. 🙈
• CHECK ( expression ) [ NO INHERIT ] — the CHECK clause specifies an expression that produces a Boolean result, and new or updated rows have to satisfy it for an insert or update operation to succeed. Expressions evaluating to TRUE or UNKNOWN succeed. If any row of an insert or update operation produces FALSE, 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, and they can't 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 get 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 — chaotic era, glad we're past it. 💀)

• 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 aren't allowed either. And the data type of the default expression must match the data type of the column. 👑

The default expression gets used in any insert operation that doesn't specify a value for the column. If there's 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 you get back the result of the specified expression. ✨

The keyword STORED is required — it signifies that the column will be computed on write and will be stored on disk.

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

• GENERATED { ALWAYS | BY DEFAULT } AS IDENTITY [ ( sequence_options ) ] — this clause creates the column as an identity column. It gets an implicit sequence attached to it, and in newly-inserted rows the column automatically has 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 — no notes.)

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 overrides 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 let you pick 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 has 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. A unique table constraint behaves exactly like a unique column constraint, except it can span multiple columns. So the constraint enforces that any two rows must differ in at least one of those 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's different from the set named by any other unique or primary key constraint defined for the table. (Otherwise, redundant unique constraints get discarded.)

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

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

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

These next clauses are literally the personality of your table — buckle up, bestie. 💅

💖 PRIMARY KEY — column constraint + table constraint

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

Okay so the PRIMARY KEY constraint says a column or columns in a table can only hold unique (non-duplicate), nonnull values. And no cap: only one primary key can be specified for a table, whether you do it as a column constraint or a table constraint. 👑

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

PRIMARY KEY enforces the 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, since a primary key implies that other tables can rely on this set of columns as a unique identifier for rows. That's main character energy for your schema, fr fr. ✨

When placed on a partitioned table, PRIMARY KEY constraints share the restrictions previously described for UNIQUE constraints. Keep that in mind. 🫶

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

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… don't forget they're attached, iykyk. 🎀

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🦋 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 bestie, 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, 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. Periodt. 👑

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. Do not skip the parentheses, bestie — that's the vibe check. 🫶

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🌈 REFERENCES / FOREIGN KEY — column constraint + table constraint

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

These clauses specify a foreign key constraint, which requires that a group of one or more columns of the new table must only contain values that match values in the referenced column(s) of some row of the referenced table. If the refcolumn list is omitted, the primary key of the reftable is used. Otherwise, the refcolumn list must refer to the columns of a non-deferrable unique or primary key constraint or be the columns of a non-partial unique index. The user must have REFERENCES permission on the referenced table (either the whole table, or the specific referenced columns). 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. This one is the default, bestie. 💖
• 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.)

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. 🫠

Okay, important warning moment: those referential actions? They cannot be deferred unless we're talking about the NO ACTION check. Even if you declared the constraint deferrable, the other actions still do their thing. 💀

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 dramatic consequences, no cap. 🔥
• 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.) 🎀

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. Lowkey a glow-up for performance. ✨

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🧚 DEFERRABLE / NOT DEFERRABLE

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. Ik, lots of rules — but that's the gig. 💅

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🎀 INITIALLY IMMEDIATE / INITIALLY DEFERRED

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. So you can vibe-check it later, basically. 🦋

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🌸 USING method

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. 🫶

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💜 WITH clause

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. Nostalgia but make it deprecated. 😭

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⭐ WITHOUT OIDS

WITHOUT OIDS

This is backward-compatible syntax for declaring a table WITHOUT OIDS, creating a table WITH OIDS is not supported anymore. So yeah — that era is over, bestie. 🕰️

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🌈 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 — bestie, this is you picking where the new table actually lives on disk 💾. tablespace_name is the name of the tablespace the new table gets created in. Don't specify it? Then default_tablespace gets consulted, or temp_tablespaces if the table is temporary. And for partitioned tables — okay this is the cute part — since no storage is required for the table itself, the tablespace you name here overrides default_tablespace as the default tablespace used for any newly created partitions when no other tablespace is explicitly specified. Iconic override behavior, no cap ✨
• USING INDEX TABLESPACE tablespace_name — this clause lets you select the tablespace where the index associated with a UNIQUE, PRIMARY KEY, or EXCLUDE constraint gets created 🎀. If you don't specify it, default_tablespace is consulted, or temp_tablespaces if the table is temporary.

🧚 Storage Parameters 🧚

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? Documented in CREATE INDEX (CREATE_INDEX(7)), go look. The storage parameters currently available for tables are listed below, bestie, and yes there's a lot, we're getting through all of them 💅.

For many of these parameters, as shown, there's an additional parameter with the same name prefixed with toast. — that one 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 use the table's parameter value 🫶. Specifying these parameters for partitioned tables is not supported — but you may specify them for individual leaf partitions. Noted, moving on.

• 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, and 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 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. This parameter cannot be set for TOAST tables. 🙈
• toast_tuple_target (integer) — 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 — 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. Also, lowkey: 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) — sets the number of workers that should be used to assist a parallel scan of this table 🔥. If not set, the system determines 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. Like, it's a suggestion, not a promise, bestie.
• autovacuum_enabled, toast.autovacuum_enabled (boolean) — enables or disables the autovacuum daemon for a particular table 🧹. If true, the autovacuum daemon performs 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 doesn't 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. Yeah. Only false matters. 💀
• 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's enabled; and with AUTO, a decision is made dynamically, each time VACUUM runs ✨. That dynamic behavior lets VACUUM avoid needlessly scanning indexes to remove very few dead tuples. 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 🎀. Heads up though: the truncation requires an ACCESS EXCLUSIVE lock on the table 🫶. 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.

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📝 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. (See CREATE INDEX (CREATE_INDEX(7)) for more info, bestie.)

Unique constraints and primary keys are not inherited in the current implementation 💀. Which makes the combination of inheritance and unique constraints rather dysfunctional. Yeah. It's giving "we know."

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

✨ EXAMPLES ✨

Okay bestie, let's actually build some tables. First up: making films and distributors — the classic little duo.

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 <> '')
);

Now a table with a 2-dimensional array. Yes, arrays can have dimensions, and this is giving data-structure main character energy:

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

Wanna define a unique table constraint for the table films? Unique table constraints can be defined on one or more columns of the table, and it looks like this:

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)
);

Next: a check column constraint. Little inline rule, doing its thing:

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

And here's a check table constraint — same idea, but it gets the table-level treatment:

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

Define a primary key table constraint for the table films? Say less, here's the code:

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)
);

Now define a primary key constraint for table distributors. The following two examples are equivalent — the first uses the table constraint syntax, the second uses the column constraint syntax. Both are valid, bestie:

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

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

Assign a literal constant default value for the column name, arrange for the default value of column did to be generated by selecting the next value of a sequence object, and make the default value of modtime be the time at which the row is inserted. Defaults are literally the "set it and forget it" of table columns:

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

Define two NOT NULL column constraints on the table distributors, one of which is explicitly given a name. Ngl, naming your constraints is such a flex:

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

Define a unique constraint for the name column. Tiny but mighty:

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

The same thing, but specified as a table constraint. Same energy, different syntax:

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. Fill factor said "I deserve a little mention too":

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

Create table circles with an exclusion constraint that prevents any two circles from overlapping. This is the "personal space" constraint, and honestly? Respect:

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

Create table cinemas in tablespace diskvol1. Location, location, location:

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

Create a composite type and a typed table. Type girlies, rise:

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

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

Create a range partitioned table. Partitioning is that girl:

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. Two columns in the key, because one was simply not enough:

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. It's giving curated list, very aesthetic:

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. Hashing it out, literally:

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

Create partition of a range partitioned table. This one gets its own little slice of the range:

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. Multi-column partition key, multi-partition moment:

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. Constraint included, because we stay safe out here:

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. Partition-ception, no cap:

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. Modulus and remainder, doing their coordinated lil dance:

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 of the partition world:

CREATE TABLE cities_partdef
    PARTITION OF cities DEFAULT;

🦋 COMPATIBILITY 🦋

Okay bestie, so CREATE TABLE is standard-compliant overall — but there are a few exceptions, and we're about to go through every single one. No skipping, no cap. 💅

💖 Temporary Tables 💖

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

The standard's definition of temporary-table behavior is widely ignored, and PostgreSQL's behavior here is similar to several other SQL databases. 🌸

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

For compatibility's sake, PostgreSQL will accept the GLOBAL and LOCAL keywords in a temporary table declaration, but they currently have no effect. Use of these keywords is discouraged, since future versions of PostgreSQL might adopt a more standard-compliant interpretation of their meaning. So like… don't get attached. 🙈

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

💀 Non-Deferred Uniqueness Constraints 💀

When a UNIQUE or PRIMARY KEY constraint is not deferrable, PostgreSQL checks for uniqueness immediately whenever a row is inserted or modified. The SQL standard says that uniqueness should be enforced only at the end of the statement; this makes a difference when, for example, a single command updates multiple key values. To obtain standard-compliant behavior, declare the constraint as DEFERRABLE but not deferred (i.e., INITIALLY IMMEDIATE). Be aware that this can be significantly slower than immediate uniqueness checking. So yeah, standard behavior comes with a little performance tax. 😭

🌈 Column Check Constraints 🌈

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

🎀 EXCLUDE Constraint 🎀

The EXCLUDE constraint type is a PostgreSQL extension. Periodt.

🦋 Foreign Key Constraints 🦋

The ability to specify column lists in the foreign key actions SET DEFAULT and SET NULL is a PostgreSQL extension. ✨

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

🍓 NULL “Constraint” 🍓

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

👑 Constraint Naming 👑

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

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

🌸 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 love a family tree, but this one's built different. 🌈

💜 Zero-Column Tables 💜

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

💖 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, you can, but the vibes are complicated. 😭

🧚 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. So PostgreSQL is out here doing its own thing, but it's not alone. 🫶

⭐ 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. Overlap? Yes. Exact match? Absolutely not. 💅

🔥 WITH Clause 🔥

The WITH clause is a PostgreSQL extension; storage parameters are not in the standard. That's the whole note. Short and slay. ✨

🌈 Tablespaces 🌈

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

🦋 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 we're doing a subset, and that part is a no. 🙈

💅 PARTITION BY Clause 💅

The PARTITION BY clause is a PostgreSQL extension. Periodt.

🎀 PARTITION OF Clause 🎀

The PARTITION OF clause is a PostgreSQL extension. Also periodt.

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🌟 SEE ALSO 🌟

• ALTER TABLE (ALTER_TABLE(7)) 💖
• DROP TABLE (DROP_TABLE(7)) 🦋
• CREATE TABLE AS (CREATE_TABLE_AS(7)) ✨
• CREATE TABLESPACE (CREATE_TABLESPACE(7)) 🌸
• CREATE TYPE (CREATE_TYPE(7)) 🎀

That's the whole compatibility saga, bestie: this iconic page is from PostgreSQL 15.19, dated 2026, and it's CREATE TABLE(7) — go forth and make tables with main-character energy. 💅🔥🎀