Preamble
PostgreSQL IS NULL condition is used to check the value of NULL in SELECT, INSERT, UPDATE or DELETE operators.
PostgreSQL IS NULL condition
IS expression NULL
Parameters and arguments
- expression – A value to check if it is a NULL value.
Note:
- If the expression is NULL, the condition is evaluated as TRUE.
- If the expression is not a value of NULL, the condition is evaluated as FALSE.
Example of an IS NULL condition with the SELECT operator
Let’s consider an example of using PostgreSQL IS NULL in the SELECT operator:
SELECT *
FROM empls
WHERE first_number IS NULL;
This example of PostgreSQL IS NULL will return all records from the employee table where first_name contains the value NULL.
Example of a condition with the INSERT operator
Then let’s consider an example of using PostgreSQL IS NULL in the INSERT operator:
INSERT INTO contacts
(first_name, last_name)
SELECT first_name, last_name
FROM empls
WHERE empl_number IS NULL;
This example of PostgreSQL IS NULL will insert records into the contacts table where employee_number contains the value NULL.
Example of a condition with UPDATE operator
Next Let’s consider an example of using PostgreSQL IS NULL in UPDATE operator:
UPDATE empls
SET status = 'Not Active'
WHERE last_name IS NULL;
This example of PostgreSQL IS NULL will update records in the employee table where last_name contains the value NULL.
Example of a condition with the DELETE operator
Next Let’s consider an example of using PostgreSQL IS NULL in DELETE operator:
DELETE FROM empls
WHERE empl_number IS NULL;
This example of PostgreSQL IS NULL will remove all records from the contacts table where employee_number contains the value NULL.
PostgreSQL: Coalesce | 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 Can Enterprises Reduce Database Costs Without Sacrificing Performance?
- 11 September 2026
- Database Performance Management
Enterprises can reduce database costs without sacrificing performance by identifying inefficient SQL, right-sizing infrastructure, eliminating unused capacity, analyzing workload patterns, improving storage efficiency, and using database observability to connect resource consumption with application performance. Database cost optimization helps organizations control infrastructure spending while Enteros UpBeat provides performance intelligence, workload visibility, predictive analytics, and Cloud FinOps … Continue reading “How Can Enterprises Reduce Database Costs Without Sacrificing Performance?”
How Can AI Detect Database Performance Anomalies Before They Cause Downtime?
AI can detect database performance anomalies by continuously analyzing workload patterns, SQL behavior, latency, resource usage, waits, and historical baselines. AI database anomaly detection helps identify unusual behavior before it becomes a larger outage. With Enteros UpBeat, IT teams can detect emerging issues earlier, investigate root causes faster, and improve database reliability across complex enterprise … Continue reading “How Can AI Detect Database Performance Anomalies Before They Cause Downtime?”
How Can Financial Institutions Detect Database Bottlenecks Before Transaction Delays Occur?
- 10 September 2026
- Database Performance Management
Financial institutions can detect database bottlenecks before transaction delays occur by continuously monitoring query latency, database waits, CPU, memory, I/O, locking, workload changes, and transaction throughput. By combining performance baselines, anomaly detection, SQL intelligence, predictive analytics, and automated root cause analysis, teams can identify emerging issues early and optimize databases before customer-facing banking, payment, or … Continue reading “How Can Financial Institutions Detect Database Bottlenecks Before Transaction Delays Occur?”
What Role Does AI-Powered Database Monitoring for Banking Play in Performance Management?
AI-powered database monitoring for banking helps financial institutions detect anomalies, identify performance bottlenecks, analyse SQL workloads, predict capacity risks, and accelerate troubleshooting. By combining database observability with automated analysis, AI-powered database performance supports faster incident response, more reliable transactions, better resource utilisation, stronger capacity planning, and smarter cloud cost decisions across increasingly complex banking database … Continue reading “What Role Does AI-Powered Database Monitoring for Banking Play in Performance Management?”