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Chapter 8. Data 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 8-1 shows all built-in general-purpose data types. 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 8-1. Data Types

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 the plane
bytea   binary data
character varying(n) varchar(n) variable-length character string
character(n) char(n) fixed-length character string
cidr   IPv4 or IPv6 network address
circle   circle in the plane
date   calendar date (year, month, day)
double precision float8 double precision floating-point number
inet   IPv4 or IPv6 host address
integer int, int4 signed four-byte integer
interval(p)   time span
line   infinite line in the plane (not fully implemented)
lseg   line segment in the 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 the plane
point   geometric point in the plane
polygon   closed geometric path in the 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 varying, character, varchar, date, double precision, integer, interval, numeric, decimal, real, smallint, time (with or without time zone), timestamp (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. Some of the input and output functions are not invertible. That is, the result of an output function may lose accuracy 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 cause underflow or overflow.

8.1. Numeric Types

Numeric types consist of two-, four-, and eight-byte integers, four- and eight-byte floating-point numbers, and fixed-precision decimals. Table 8-2 lists the available types.

Table 8-2. Numeric Types

Name Storage Size Description Range
smallint 2 bytes small-range integer -32768 to +32767
integer 4 bytes usual choice for integer -2147483648 to +2147483647
bigint 8 bytes large-range integer -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 4.1.2. The numeric types have a full set of corresponding arithmetic operators and functions. Refer to Chapter 9 for more information. The following sections describe the types in detail.

8.1.1. Integer Types

The types smallint, integer, and 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.

8.1.2. Arbitrary Precision Numbers

The type numeric can store numbers with up to 1000 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.

8.1.3. 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 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.

On most platforms, 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 typically has a range of around 1E-307 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.

PostgreSQL also supports the SQL-standard notations float and float(p) for specifying inexact numeric types. Here, p specifies the minimum acceptable precision in binary digits. PostgreSQL accepts float(1) to float(24) as selecting the real type, while float(25) to float(53) select double precision. Values of p outside the allowed range draw an error. float with no precision specified is taken to mean double precision.

Note: Prior to PostgreSQL 7.4, the precision in float(p) was taken to mean so many decimal digits. This has been corrected to match the SQL standard, which specifies that the precision is measured in binary digits. The assumption that real and double precision have exactly 24 and 53 bits in the mantissa respectively is correct for IEEE-standard floating point implementations. On non-IEEE platforms it may be off a little, but for simplicity the same ranges of p are used on all platforms.

8.1.4. Serial Types

The data types serial and bigserial are not true types, but merely a notational convenience for setting up unique identifier columns (similar to the AUTO_INCREMENT property supported by some other databases). In the current implementation, specifying

CREATE TABLE tablename (
    colname SERIAL
);

is equivalent to specifying:

CREATE SEQUENCE tablename_colname_seq;
CREATE TABLE tablename (
    colname integer DEFAULT nextval('tablename_colname_seq') NOT NULL
);

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.

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

To insert the next value of the sequence into the serial column, specify that the serial column should be assigned its default value. This can be done either by excluding the column from the list of columns in the INSERT statement, or through the use of the DEFAULT key word.

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 231 identifiers over the lifetime of the table.

The sequence created for a serial column 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.) Furthermore, this dependency between sequence and column is made only for the serial column itself; if any other columns reference the sequence (perhaps by manually calling the nextval function), they will be broken if the sequence is removed. Using a serial column's sequence in such a fashion is considered bad form; if you wish to feed several columns from the same sequence generator, create the sequence as an independent object.

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