PostgreSQL Mathematical Functions: Enhancing Coding Efficiency

Mathematical functions are an essential part of any programming language or database system. They provide developers with ready-to-use solutions for performing mathematical calculations, thereby increasing coding efficiency and accuracy. PostgreSQL offers a comprehensive set of mathematical functions that can significantly enhance your data-handling capabilities.

PostgreSQL's Mathematical Functions

PostgreSQL boasts a rich set of mathematical functions that handle everything from basic arithmetic to complex trigonometric calculations. These include but are not limited to ABS(), CEIL(), FLOOR(), MOD(), ROUND(), TRUNC(), and more. These functions exhibit high performance and precision, making them an invaluable tool for developers. 

The Benefits of Using PostgreSQL Mathematical Functions

Increased accuracy

PostgreSQL's mathematical functions are designed to deliver highly accurate results, reducing the likelihood of errors due to manual calculations or less efficient functions provided by other systems.

Enhanced coding efficiency

These functions allow developers to perform complex calculations directly within the database, reducing the need for external computations and speeding up execution time.

Real-World Use Cases of PostgreSQL's Mathematical Functions

Let's take a look at some examples of how these functions can be applied to real-world programming projects:

  • E-commerce applications: The ROUND() function can be used to calculate the total cost of items in a shopping cart, including taxes and discounts.

  • Financial systems: The CEIL() and FLOOR() functions can be used for rounding up or down monetary values to the nearest whole number.

  • Data analysis tools: The MOD() function can be used to categorize data into different buckets based on certain criteria.

List of PostgreSQL Mathematical Functions


The ABS() function returns the absolute value of a number.


SELECT ABS(-10); -- Returns 10


The CEIL() or CEILING() function rounds a number up to the nearest integer.


SELECT CEIL(7.4); -- Returns 8

MOD(n, m)

The MOD() function returns the remainder of n divided by m.


SELECT MOD(10, 3); -- Returns 1


The FLOOR() function rounds a number down to the nearest integer.


SELECT FLOOR(7.8); -- Returns 7

ROUND(number, [decimals])

The ROUND() function rounds a number to a certain number of decimal places. If the decimals parameter is omitted, it rounds to the nearest whole number.


SELECT ROUND(7.456, 2); -- Returns 7.46

TRUNC(number, [decimals])

The TRUNC() function truncates a number to a certain number of decimal places without rounding. If the decimals parameter is omitted, it truncates to the nearest whole number.


SELECT TRUNC(7.456, 2); -- Returns 7.45

A Summary on PostgreSQL Mathematical Functions

Postgres’ mathematical functions offer benefits such as increased accuracy and enhanced coding efficiency, and their wide range of applications makes them a must-know for anyone working with PostgreSQL.

For further reading and a deeper understanding of these functions, you can visit the official PostgreSQL documentation or read our next article on aggregate functions.

Remember, the key to mastering these functions lies in practice. So, dive into your PostgreSQL database and start crunching those numbers!

Use Timescale Functions for Hyper Speed and Ease 

Now that you’ve learned the basics of PostgreSQL functions, it’s time for a better alternative. Hyperfunctions are a series of SQL functions within TimescaleDB that make it easier to manipulate and analyze time-series data in PostgreSQL with fewer lines of code. 

You can use hyperfunctions to calculate percentile approximations of data, compute time-weighted averages, downsample and smooth data, and perform faster COUNT DISTINCT queries using approximations. Moreover, hyperfunctions are simple to use: you call a hyperfunction using the same SQL syntax you know and love. 

Learn more about hyperfunctions on our Docs page, or keep reading for more information on window functions.