PostgreSQL NUMERIC Type

Summary: in this tutorial, you will learn about the PostgreSQL NUMERIC type for storing numeric data.

Introduction to PostgreSQL NUMERIC data type

The NUMERIC type can store numbers with a lot of digits. Typically, you use the NUMERIC type for storing numbers that require exactness such as monetary amounts or quantities.

Here’s the syntax for declaring a column with the NUMERIC type:

column_name NUMERIC(precision, scale)

In this syntax:

• The precision is the total number of digits
• The scale is the number of digits in the fraction part.

The storage type of the numeric type depends on the precision and scale.

The NUMERIC type can hold a value of up to 131,072 digits before the decimal point 16,383 digits after the decimal point.

The scale of the NUMERIC type can be zero, positive, or negative.

PostgreSQL 15 or later allows you to declare a numeric column with a negative scale.

The following declares the price column with the numeric type that can store total numbers with 7 digits, 5 before the decimal points and 2 digits after the decimal point:

price NUMERIC(7,2)

If you use a negative scale, you can store up to precision + scale digits on the left and no digits on the right of the decimal point. For example:

amount NUMERIC(5,-2)

In this example, you can store up to 7 digits before and 0 digits after the decimal point.

The following example shows how to declare a column of type numeric with a zero scale:

quantity NUMERIC(5, 0)

It’s equivalent to the following declaration that does not explicitly specify the zero scale:

quantity NUMERIC(5)

If you omit precision and scale, they will default to 131072 and 16383, respectively.

NUMERIC

NUMERIC, DECIMAL, and DEC types

In PostgreSQL, the NUMERIC and DECIMAL types are synonyms so you can use them interchangeably:

DECIMAL(p,s)

If you prefer a shorter name, you can use the name DEC because DEC and DECIMAL are the same type:

DEC(p,s)

If precision is not required, you should not use the NUMERIC type because calculations on NUMERIC values are typically slower than integers, float, and double precisions.

Special values

Besides the ordinal numeric values, the numeric type has several special values:

• Infinity
• -Infinity
• NaN

These values represent “infinity”, “negative infinity”, and “not-a-number”, respectively.

PostgreSQL NUMERIC data type examples

Let’s take some examples of using the PostgreSQL NUMERIC type.

1) Storing numeric values

If you store a value with a scale greater than the declared scale of the NUMERIC column, PostgreSQL will round the value to a specified number of fractional digits. For example:

First, create a new table called products:

CREATE TABLE products (
    id SERIAL PRIMARY KEY,
    name VARCHAR(100) NOT NULL,
    price NUMERIC(5,2)
);

Second, insert some products with prices whose scales exceed the scale declared in the price column:

INSERT INTO products (name, price)
VALUES ('Phone',500.215),
       ('Tablet',500.214);

Because the scale of the price column is 2, PostgreSQL rounds the value 500.215 up to 500.22 and rounds the value 500.214 down to 500.21 :

The following query returns all rows of the products table:

SELECT * FROM products;

Output:

id |  name  | price
----+--------+--------
  1 | Phone  | 500.22
  2 | Tablet | 500.21
(2 rows)

If you store a value whose precision exceeds the declared precision, PostgreSQL will raise an error as shown in the following example:

INSERT INTO products (name, price)
VALUES('Phone',123456.21);

PostgreSQL issued the following error:

ERROR:  numeric field overflow
DETAIL:  A field with precision 5, scale 2 must round to an absolute value less than 10^3.

2) PostgreSQL NUMERIC type and NaN

In addition to holding numeric values, the NUMERIC type can also hold a special value called NaN which stands for not-a-number.

The following example updates the price of product id 1 to NaN :

UPDATE products
SET price = 'NaN'
WHERE id = 1;

Notice that you must use single quotes to wrap the NaN as shown in the UPDATE statement above.

The following query returns the data of the products table:

SELECT * FROM products;

Output:

id |  name  | price
----+--------+--------
  2 | Tablet | 500.21
  1 | Phone  |    NaN
(2 rows)

Typically, the NaN is not equal to any number including itself. It means that the expression NaN = NaN returns false. You’ll find this implementation [in JavaScript for NaN](https://www.javascripttutorial.net/javascript-nan/).

But in PostgreSQL, two NaN values are equal. Also, NaN values are greater than regular numbers such as 1, 2, 3. This implementation allows PostgreSQL to sort NUMERIC values and use them in tree-based indexes.

The following query sorts the products based on prices from high to low:

SELECT * FROM products
ORDER BY price DESC;

Output:

id |  name  | price
----+--------+--------
  1 | Phone  |    NaN
  2 | Tablet | 500.21
(2 rows)

The output indicates that the NaN is greater than 500.21

Summary

• Use the PostgreSQL NUMERIC data type to store numbers that require exactness.