PostgreSQL has a rich set of native data
types available to users.
Users may add new types to PostgreSQL using the
CREATE TYPE command.

Table 5-1 shows all general-purpose data types
included in the standard distribution. Most of the alternative names
listed in the
"Aliases" column are the names used internally by
PostgreSQL for historical reasons. In
addition, some internally used or deprecated types are available,
but they are not listed here.

Table 5-1. Data Types

Type Name

Aliases

Description

bigint

int8

signed eight-byte integer

bigserial

serial8

autoincrementing eight-byte integer

bit

fixed-length bit string

bit varying(n)

varbit(n)

variable-length bit string

boolean

bool

logical Boolean (true/false)

box

rectangular box in 2D plane

bytea

binary data

character(n)

char(n)

fixed-length character string

character varying(n)

varchar(n)

variable-length character string

cidr

IP network address

circle

circle in 2D plane

date

calendar date (year, month, day)

double precision

float8

double precision floating-point number

inet

IP host address

integer

int, int4

signed four-byte integer

interval(p)

general-use time span

line

infinite line in 2D plane (not implemented)

lseg

line segment in 2D plane

macaddr

MAC address

money

currency amount

numeric [ (p,
s) ]

decimal [ (p,
s) ]

exact numeric with selectable precision

path

open and closed geometric path in 2D plane

point

geometric point in 2D plane

polygon

closed geometric path in 2D plane

real

float4

single precision floating-point number

smallint

int2

signed two-byte integer

serial

serial4

autoincrementing four-byte integer

text

variable-length character string

time [ (p) ] [ without time zone ]

time of day

time [ (p) ] with time zone

timetz

time of day, including time zone

timestamp [ (p) ] without time zone

timestamp

date and time

timestamp [ (p) ] [ with time zone ]

timestamptz

date and time, including time zone

Compatibility: The following types (or spellings thereof) are specified by
SQL: bit, bit
varying, boolean, char,
character, character varying,
varchar, date, double
precision, integer, interval,
numeric, decimal, real,
smallint, time, timestamp
(both with or without time zone).

Each data type has an external representation determined by its input
and output functions. Many of the built-in types have
obvious external formats. However, several types are either unique
to PostgreSQL, such as open and closed
paths, or have several possibilities for formats, such as the date
and time types.
Most of the input and output functions corresponding to the
base types (e.g., integers and floating-point numbers) do some
error-checking.
Some of the input and output functions are not invertible. That is,
the result of an output function may lose precision when compared to
the original input.

Some of the operators and functions (e.g.,
addition and multiplication) do not perform run-time error-checking in the
interests of improving execution speed.
On some systems, for example, the numeric operators for some data types may
silently underflow or overflow.

Numeric types consist of two-, four-, and eight-byte integers,
four- and eight-byte floating-point numbers, and fixed-precision
decimals. Table 5-2 lists the
available types.

Table 5-2. Numeric Types

Type name

Storage size

Description

Range

smallint

2 bytes

small range fixed-precision

-32768 to +32767

integer

4 bytes

usual choice for fixed-precision

-2147483648 to +2147483647

bigint

8 bytes

large range fixed-precision

-9223372036854775808 to 9223372036854775807

decimal

variable

user-specified precision, exact

no limit

numeric

variable

user-specified precision, exact

no limit

real

4 bytes

variable-precision, inexact

6 decimal digits precision

double precision

8 bytes

variable-precision, inexact

15 decimal digits precision

serial

4 bytes

autoincrementing integer

1 to 2147483647

bigserial

8 bytes

large autoincrementing integer

1 to 9223372036854775807

The syntax of constants for the numeric types is described in
Section 1.1.2. The numeric types have a
full set of corresponding arithmetic operators and
functions. Refer to Chapter 6 for more
information. The following sections describe the types in detail.

The types smallint, integer,
bigint store whole numbers, that is, numbers without
fractional components, of various ranges. Attempts to store
values outside of the allowed range will result in an error.

The type integer is the usual choice, as it offers
the best balance between range, storage size, and performance.
The smallint type is generally only used if disk
space is at a premium. The bigint type should only
be used if the integer range is not sufficient,
because the latter is definitely faster.

The bigint type may not function correctly on all
platforms, since it relies on compiler support for eight-byte
integers. On a machine without such support, bigint
acts the same as integer (but still takes up eight
bytes of storage). However, we are not aware of any reasonable
platform where this is actually the case.

SQL only specifies the integer types
integer (or int) and
smallint. The type bigint, and the
type names int2, int4, and
int8 are extensions, which are shared with various
other SQL database systems.

Note: If you have a column of type smallint or
bigint with an index, you may encounter problems
getting the system to use that index. For instance, a clause of
the form

... WHERE smallint_column = 42

will not use an index, because the system assigns type
integer to the constant 42, and
PostgreSQL currently
cannot use an index when two different data types are involved. A
workaround is to single-quote the constant, thus:

... WHERE smallint_column = '42'

This will cause the system to delay type resolution and will
assign the right type to the constant.

The type numeric can store numbers with up to 1,000
digits of precision and perform calculations exactly. It is
especially recommended for storing monetary amounts and other
quantities where exactness is required. However, the
numeric type is very slow compared to the
floating-point types described in the next section.

In what follows we use these terms: The
scale of a numeric is the
count of decimal digits in the fractional part, to the right of
the decimal point. The precision of a
numeric is the total count of significant digits in
the whole number, that is, the number of digits to both sides of
the decimal point. So the number 23.5141 has a precision of 6
and a scale of 4. Integers can be considered to have a scale of
zero.

Both the precision and the scale of the numeric type can be
configured. To declare a column of type numeric use
the syntax

NUMERIC(precision, scale)

The precision must be positive, the scale zero or positive.
Alternatively,

NUMERIC(precision)

selects a scale of 0. Specifying

NUMERIC

without any precision or scale creates a column in which numeric
values of any precision and scale can be stored, up to the
implementation limit on precision. A column of this kind will
not coerce input values to any particular scale, whereas
numeric columns with a declared scale will coerce
input values to that scale. (The SQL standard
requires a default scale of 0, i.e., coercion to integer
precision. We find this a bit useless. If you're concerned
about portability, always specify the precision and scale
explicitly.)

If the precision or scale of a value is greater than the declared
precision or scale of a column, the system will attempt to round
the value. If the value cannot be rounded so as to satisfy the
declared limits, an error is raised.

The types decimal and numeric are
equivalent. Both types are part of the SQL
standard.

The data types real and double
precision are inexact, variable-precision numeric types.
In practice, these types are usually implementations of
IEEE Standard 754 for Binary Floating-Point
Arithmetic (single and double precision, respectively), to the
extent that the underlying processor, operating system, and
compiler support it.

Inexact means that some values cannot be converted exactly to the
internal format and are stored as approximations, so that storing
and printing back out a value may show slight discrepancies.
Managing these errors and how they propagate through calculations
is the subject of an entire branch of mathematics and computer
science and will not be discussed further here, except for the
following points:

If you require exact storage and calculations (such as for
monetary amounts), use the numeric type instead.

If you want to do complicated calculations with these types
for anything important, especially if you rely on certain
behavior in boundary cases (infinity, underflow), you should
evaluate the implementation carefully.

Comparing two floating-point values for equality may or may
not work as expected.

Normally, the real type has a range of at least
-1E+37 to +1E+37 with a precision of at least 6 decimal digits. The
double precision type normally has a range of around
-1E+308 to +1E+308 with a precision of at least 15 digits. Values that
are too large or too small will cause an error. Rounding may
take place if the precision of an input number is too high.
Numbers too close to zero that are not representable as distinct
from zero will cause an underflow error.

The serial data types are not truly types, but are a
notational convenience for setting up unique identifier columns
in tables.
In the current implementation, specifying

Thus, we have created an integer column and arranged for its default
values to be assigned from a sequence generator. A NOT NULL
constraint is applied to ensure that a null value cannot be explicitly
inserted, either. In most cases you would also want to attach a
UNIQUE or PRIMARY KEY constraint to prevent
duplicate values from being inserted by accident, but this is
not automatic.

The type names serial and serial4 are
equivalent: both create integer columns. The type
names bigserial and serial8 work just
the same way, except that they create a bigint
column. bigserial should be used if you anticipate
the use of more than 2^{31} identifiers over the lifetime of the table.

The sequence created by a serial type is automatically
dropped when
the owning column is dropped, and cannot be dropped otherwise.
(This was not true in PostgreSQL releases
before 7.3. Note that this automatic drop linkage will not occur for a
sequence created by reloading a dump from a pre-7.3 database; the dump
file does not contain the information needed to establish the dependency
link.)

Note: Prior to PostgreSQL 7.3, serial
implied UNIQUE. This is no longer automatic. If
you wish a serial column to be UNIQUE or a
PRIMARY KEY it must now be specified, same as with
any other data type.