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,

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 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:

• 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.

3.1.4. The Serial Types

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

CREATE TABLE tablename (
    colname SERIAL
);

is equivalent to specifying:

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

Thus, we have created an integer column and arranged for its default values to be assigned from a sequence generator. UNIQUE and NOT NULL constraints are applied to ensure that explicitly-inserted values will never be duplicates, either.

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 use of more than 2³¹ identifiers over the lifetime of the table.

Implicit sequences supporting the serial types are not automatically dropped when a table containing a serial type is dropped. So, the following commands executed in order will likely fail:

CREATE TABLE tablename (colname SERIAL);
DROP TABLE tablename;
CREATE TABLE tablename (colname SERIAL);

The sequence will remain in the database until explicitly dropped using DROP SEQUENCE. (This annoyance will probably be changed in some future release.)