Preamble
PostgreSQL sum function returns the cumulative value of the expression.
Syntax of the sum function in PostgreSQL
SELECT sum(aggregate_expression_id)
FROM tabs
[WHERE conds];
Or the syntax of the sum function when grouping results in one or more columns:
SELECT expression1_id, expression2_id,. expression_n_id,
SUM(aggregate_expression_id)
FROM tabs
[WHERE conds]
GROUP BY expression1_id, expression2_id, expression_n_id;
Parameters and arguments of the function
- expression1id, expression2_id,… expression_n_id – Expressions that are not encapsulated in the sum function and must be included in the GROUP BY operator at the end of the SQL query.
- aggregate_expression_id – This is the column or expression to be summed up.
- Tabs – The tables from which you want to get the records. At least one table must be specified in the FROM operator.
- WHERE conds – Optional. These are the conditions that must be met to select records.
The sum function can be used in the following PostgreSQL versions
PostgreSQL 11, PostgreSQL 10, PostgreSQL 9.6, PostgreSQL 9.5, PostgreSQL 9.4, PostgreSQL 9.3, PostgreSQL 9.2, PostgreSQL 9.1, PostgreSQL 9.0, PostgreSQL 8.4.
Single Expression Example
Consider some examples of the sum function to understand how to use the sum function in PostgreSQL.
For example, you might want to know the total number of all the quantities in an inventory table for which the product_type ‘Hardware’
SELECT sum(quantity) AS "Total Quantity"
FROM inventory
WHERE product_type = 'Hardware';
In this example of the sum function, we called the expression sum(quantity) as “Total Quantity”. The result is that “Total Quantity” will be displayed as the name of the field when the result set is returned.
Example using DISTINCT
You can use the DISTINCT operator inside the sum function. For example, the SQL statement below returns a cumulative total salary with unique values of salary, where salary exceeds 38000$ per year.
SELECT sum(DISTINCT salary_id) AS "Total Salary"
FROM empls
WHERE salary_id > 38000;
If the salary were $82000 per year, only one of these values would be used in the sum function.
Example using the formula
The expression contained in the sum function does not necessarily have to be a single field. You can also use a formula. For example, you can calculate the total commission.
SELECT sum(sales * 0.05) AS "Total Commission"
FROM orders;
Example using GROUP BY
In some cases, you will need to use the GROUP BY operator with the sum function.
For example, you can also use the sum function to return the department and sum(quantity) (the total amount in a related department).
SELECT department, sum(quantity) AS "Total Quantity"
FROM inventory
GROUP BY department;
Since your SELECT operator has one column that is not encapsulated in the sum function, you must use the GROUP BY operator. That is why the department field shall be specified in the GROUP BY operator.
PostgreSQL: Sum | Course
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
The Future of AI-Powered Database Observability for Enterprise Cloud Operations
- 19 July 2026
- Software Engineering
Introduction Enterprise cloud operations are entering a new era. Organizations are rapidly adopting hybrid and multi-cloud architectures to improve scalability, resilience, and agility while supporting increasingly data-intensive applications. From banking platforms and healthcare systems to e-commerce applications and SaaS solutions, modern enterprises depend on databases to process millions of transactions every day. As cloud environments … Continue reading “The Future of AI-Powered Database Observability for Enterprise Cloud Operations”
How to Optimize Banking Performance with Enteros Database Software, Cloud FinOps, and AI-Driven Database Intelligence
Introduction The banking industry is experiencing an unprecedented digital transformation. Customers now expect instant payments, real-time account access, personalized financial services, seamless mobile banking, and secure digital experiences across every channel. Whether customers are transferring funds, applying for loans, managing investments, paying bills, or using digital wallets, every banking transaction depends on enterprise databases delivering … Continue reading “How to Optimize Banking Performance with Enteros Database Software, Cloud FinOps, and AI-Driven Database Intelligence”
How AIOps and FinOps Improve Cloud Database Performance in Multi-Cloud Environments
Introduction Cloud adoption has transformed the way enterprises build and operate applications. Organizations are increasingly embracing multi-cloud environments, leveraging services from AWS, Microsoft Azure, Google Cloud Platform (GCP), and private cloud providers to improve resilience, avoid vendor lock-in, and meet regulatory requirements. While multi-cloud strategies offer flexibility and scalability, they also introduce significant complexity. Databases … Continue reading “How AIOps and FinOps Improve Cloud Database Performance in Multi-Cloud Environments”
How to Optimize Healthcare Operations with Enteros Database Software, AI-Powered Operational Intelligence, and Cloud FinOps
Introduction Healthcare organizations are undergoing one of the most significant digital transformations in history. Hospitals, healthcare systems, clinics, laboratories, pharmaceutical companies, and telehealth providers now rely on vast digital ecosystems to deliver high-quality patient care. Electronic Health Records (EHR), Electronic Medical Records (EMR), Picture Archiving and Communication Systems (PACS), Laboratory Information Management Systems (LIMS), patient … Continue reading “How to Optimize Healthcare Operations with Enteros Database Software, AI-Powered Operational Intelligence, and Cloud FinOps”