Preamble
PostgreSQL DISTINCT statement is used to remove duplicates from the result set. DISTINCT can be used only with SELECT operators.
Syntax for DISTINCT statement in PostgreSQL
SELECT DISTINCT | DISTINCT ON (distinct_expressions_id)
expressions_id
FROM tabs
[WHERE conds];
Parameters and statement arguments
- Expressions_expressions_id – Expressions used to delete duplicates.
- Column – The column or calculation you want to get.
- tabs – The tables from which you want to get the records. The FROM operator must specify at least one table.
- WHERE conds – Optional. The conditions to be met for the records to be selected.
Note:
- If only one expression is specified in DISTINCT, the query will return unique values for that expression.
- If several expressions are specified in DISTINCT, the query retrieves the unique combinations for the listed expressions.
- If DISTINCT ON keywords are specified, the query will return unique values for Different_expressions and other fields for the selected entries based on ORDER BY (limit 1).
- In PostgreSQL, DISTINCT does not ignore NULL values. Therefore when using DISTINCT in your SQL statement, your resulting set will contain NULL as a separate value.
Example of a DISTINCT statement with one expression
Let’s look at the simplest example of DISTINCT in PostgreSQL. We can use the DISTINCT operator to return a single field that removes duplicates from the result set.
For example:
SELECT DISTINCT last_name
FROM contacts
ORDER BY last_name;
In this PostgreSQL example, DISTINCT will return all unique last_name values from the contacts table.
An example of a DISTINCT statement with multiple expressions
Let’s see how you can use the PostgreSQL DISTINCT statement to remove duplicates from more than one field in your SELECT statement.
For example:
SELECT DISTINCT last_name, city, state
FROM contacts
ORDER BY last_name, city, state;
This example will return each unique combination of last_name, city, and state from the contacts table. In this case, DISTINCT applies to each field specified after the DISTINCT keyword and therefore returns different combinations.
Example of a DISTINCT ON statement
One thing that is unique in PostgreSQL, compared to other databases, is that you have another option when using the DISTINCT operator, which is called DISTINCT ON.
DISTINCT ON will return only the first line for DISTINCT ON (diver_expressions) based on the ORDER BY operator provided in the query. Any other fields listed in the SELECT statement will be returned for this first line. This is similar to running LIMIT in 1 for each combination of DISTINCT ON (Different_expressions).
Let’s have a closer look at how to use DISTINCT ON in a DISTINCT operator and what it returns.
In this way, we could change the example above :
SELECT DISTINCT ON (last_name) last_name, city, state
FROM contacts
ORDER BY last_name, city, state;
This DISTINCT example, which uses DISTINCT ON keywords, will return all unique values of last_name. But in this case, for each unique value of last_name, it will return only the first unique last_name record it encounters, based on the ORDER BY operator together with the city and state values from that record.
It does not return unique combinations of last_name, city, and state. In fact, it performs a LIMIT of 1 for each DISTINCT ON (last_name) and returns the corresponding city and state values after it has selected the returned records.
PostgreSQL: Distinct | 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”