Preamble
PostgreSQL Comparison Operators are used in the WHERE sentence to determine which entries to choose. Here is a list of comparison statements that you can use in PostgreSQL :
|
Comparison operators
|
Description
|
|---|---|
|
=
|
Equally
|
|
<>
|
Does not matter
|
|
!=
|
Does not matter
|
|
>
|
More than
|
|
>=
|
More or equal
|
|
<
|
Less than
|
|
<=
|
Less or equal
|
|
IN ()
|
Corresponds to the value in the list
|
|
NOT
|
Denies condition
|
|
BETWEEN
|
Within range (inclusive)
|
|
IS NULL
|
value NULL
|
|
NOT NULL
|
Not NULL value
|
|
LIKE
|
Comparison with % and _ pattern
|
|
EXISTS
|
Condition fulfilled if the subquery returns at least one line
|
Consider comparison operators that you can use in PostgreSQL.
Example – operator =
In PostgreSQL, you can use the = operator to check for equality in a query.
For example, you can use an = operator:
SELECT *
FROM empls
WHERE first_name = 'Frog';
In this example, the SELECT statement above returns all rows from the employee table, where first_name equals Frog.
Example – operator =
There are two ways to check inequality in PostgreSQL. You can use the <> or != operator.
For example, we can check for inequality using the <> operator in the following way :
In this example, the SELECT operator above returns all rows from the employee table, where first_name equals Frog.
An example is the – operator
There are two ways to check inequality in PostgreSQL. You can use the <> or != operator.
For example, we can check for inequality using the <> operator in the following way :
SELECT *
FROM empls
WHERE first_name <> 'Frog';
In this example, the SELECT statement returns all rows from the employee table where first_name does not equally Frog.
Or you can also write this query using the != operator as shown below :
SELECT *
FROM empls
WHERE first_name != 'Frog';
Both these requests will return the same results.
Example – operator =
You can use the > operator in PostgreSQL to check the expression for more than that.
SELECT *
FROM products
WHERE product_id > 50;
In this example, the SELECT operator will return all rows from the products table where product_id is over 50. a product_id equal to 50 will not be included in the result set.
Example – the <= operator
In PostgreSQL, you can use the >= operator to check whether the expression is larger or equal.
SELECT *
FROM products
WHERE product_id >= 50;
In this example, the SELECT operator will return all rows from the products table where product_id is greater than or equal to 50. In this case, a product_id equal to 50 will be included in the result set.
The example is the operator <
You can use the < statement in PostgreSQL to check the expressionless.
SELECT *
FROM inventory
WHERE inventory_id < 25;
In this example, the SELECT operator will return all rows from the inventory table where inventory_id is less than 25. An inventory_id value of 25 will not be included in the result set.
Example – operator <
In PostgreSQL, you can use the <= operator to test an expression that is less than or equal.
SELECT *
FROM inventory
WHERE inventory_id <= 25;
In this example, the SELECT operator will return all rows from the inventory table where inventory_id is less than or equal to 25. In this case, n inventory_id value 25 will be included in the result set.
PostgreSQL: Comparison Operators | Course
About Enteros
IT organizations routinely spend days and weeks troubleshooting production database performance issues across multitudes of critical business systems. Fast and reliable resolution of database performance problems by Enteros enables businesses to generate and save millions of direct revenue, minimize waste of employees’ productivity, reduce the number of licenses, servers, and cloud resources and maximize the productivity of the application, database, and IT operations teams.
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
How to Optimize Media and Entertainment Database Performance with Enteros Database Software, AI-Powered Analytics, and Database Observability
- 30 August 2026
- Database Performance Management
Introduction The media and entertainment industry has become a digital-first business. Streaming services, digital publishing, online gaming content, advertising platforms, social experiences, content management systems, subscription platforms, and personalized recommendations all depend on databases. Modern media companies process enormous volumes of customer, content, advertising, transaction, and behavioral information. Read more”Indian Country” highlights Enteros and its … Continue reading “How to Optimize Media and Entertainment Database Performance with Enteros Database Software, AI-Powered Analytics, and Database Observability”
How to Optimize Manufacturing Database Performance with Enteros Database Software, AIOps, and Predictive Analytics
Introduction Manufacturing is becoming increasingly dependent on digital infrastructure. Modern factories use enterprise resource planning (ERP), manufacturing execution systems (MES), supply-chain platforms, warehouse management systems, industrial IoT, quality management applications, predictive maintenance, and advanced analytics to manage production. Behind these systems are databases processing enormous amounts of operational information. Production schedules, inventory levels, machine data, … Continue reading “How to Optimize Manufacturing Database Performance with Enteros Database Software, AIOps, and Predictive Analytics”
The Future of Industry-Specific Cloud Optimization with AIOps, FinOps, and AI-Powered Database Management
- 28 August 2026
- Database Performance Management
Introduction Cloud computing has become a foundational component of digital transformation across industries. Banking organizations use cloud platforms to support digital payments and online banking. Healthcare providers rely on cloud infrastructure for digital health applications and patient services. Educational institutions operate learning management systems and virtual classrooms in the cloud. Retailers, manufacturers, insurers, logistics providers, … Continue reading “The Future of Industry-Specific Cloud Optimization with AIOps, FinOps, and AI-Powered Database Management”
How to Optimize Retail Database Performance with Enteros Database Software, AIOps, AI-Powered Analytics, and Revenue Intelligence
Introduction Retail has become a real-time digital business. Ecommerce, mobile applications, point-of-sale systems, inventory platforms, loyalty programs, customer analytics, supply chain systems, recommendation engines, and payment platforms all depend on databases. Retailers also experience highly variable demand. Read more”Indian Country” highlights Enteros and its database performance management platform *Black Friday, holiday shopping, product launches, flash … Continue reading “How to Optimize Retail Database Performance with Enteros Database Software, AIOps, AI-Powered Analytics, and Revenue Intelligence”