Chapter 3. Data Types

Table of Contents
3.1. Numeric Types
3.1.1. The Integer Types
3.1.2. Arbitrary Precision Numbers
3.1.3. Floating-Point Types
3.1.4. The Serial Types
3.2. Monetary Type
3.3. Character Types
3.4. Binary Strings
3.5. Date/Time Types
3.5.1. Date/Time Input
3.5.2. Date/Time Output
3.5.3. Time Zones
3.5.4. Internals
3.6. Boolean Type
3.7. Geometric Types
3.7.1. Point
3.7.2. Line Segment
3.7.3. Box
3.7.4. Path
3.7.5. Polygon
3.7.6. Circle
3.8. Network Address Data Types
3.8.1. inet
3.8.2. cidr
3.8.3. inet vs cidr
3.8.4. macaddr
3.9. Bit String Types

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 3-1 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 3-1. Data Types

Type NameAliasesDescription
bigintint8signed eight-byte integer
bigserialserial8autoincrementing eight-byte integer
bit fixed-length bit string
bit varying(n)varbit(n)variable-length bit string
booleanboollogical 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 precisionfloat8double precision floating-point number
inet IP host address
integerint, int4signed four-byte integer
interval(p) general-use time span
line infinite line in 2D plane
lseg line segment in 2D plane
macaddr MAC address
money US-style currency
numeric [ (p, s) ]decimal [ (p, s) ]exact numeric with selectable precision
oid object identifier
path open and closed geometric path in 2D plane
point geometric point in 2D plane
polygon closed geometric path in 2D plane
realfloat4single precision floating-point number
smallintint2signed two-byte integer
serialserial4autoincrementing four-byte integer
text variable-length character string
time [ (p) ] [ without time zone ] time of day
time [ (p) ] with time zonetimetztime of day, including time zone
timestamp [ (p) ] without time zonetimestampdate and time
timestamp [ (p) ] [ with time zone ]timestamptzdate 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.

3.1. Numeric Types

Numeric types consist of two-, four-, and eight-byte integers, four- and eight-byte floating-point numbers and fixed-precision decimals.

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 4 for more information. The following sections describe the types in detail.

3.1.1. The Integer Types

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 RDBMS products.

3.1.2. Arbitrary Precision Numbers

The type numeric can store numbers of practically unlimited size and precision, while being able to store all numbers and carry out all 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,


selects a scale of 0. Specifying


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 accuracy. 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.

3.1.3. Floating-Point Types

The data types real and double precision are inexact, variable-precision numeric types. In practice, these types are usually implementations of IEEE 754 binary floating point (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:

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.