Preamble
The PostgreSQL UPDATE statement is used to update existing table entries in a PostgreSQL database.
The syntax for the UPDATE statement when updating a single table in PostgreSQL
UPDATE table
SET column1 = expression1_id | DEFAULT,
column2 = expression2_id | DEFAULT,
…
[WHERE conds];
Parameters and arguments of the statement
- column1, column2 – Columns that you want to update.
- expression1_id, column2_id – New values for assigning column1, column2. Therefore, column1 will be assigned the value expression1, column2 will be assigned the value2, etc.
- DEFAULT – The default value for this particular column in the table. If the default value for a column is not set, the column will be set to NULL.
- WHERE conds – Optional. The conditions that must be met to perform the update. If no conditions are set, all entries in the table will be updated.
Example of how to update a single column
Let’s look at a very simple example of a PostgreSQL UPDATE query.
UPDATE contacts
SET first_name = 'Helen'
WHERE contact_id = 35;
In this example, the value of first_name will be updated to ‘Helen’ in the contacts table, where contact_id is 35.
You can also use the keyword DEFAULT to set the default value for the column.
For example,
UPDATE contacts
SET first_name = DEFAULT
WHERE contact_id = 35;
In this example, the first_name will be updated to the default value for the field in the contacts table, where contact_id is 35. If the default value is not present in the contacts table, the first_name column will be set to NULL.
Example how to update several columns
Consider the UPDATE example for PostgreSQL, where you can update several columns with one UPDATE statement.
UPDATE contacts
SET city = 'Abilene',
state = 'Beaumont'
WHERE contact_id >= 200;
If you want to update multiple columns, you can do so by separating the column/value pairs with commas.
In this PostgreSQL example of UPDATE, the value of the city will be changed to ‘Abilene’ and the state will be changed to ‘Beaumont’ where contact_id is greater than or equal to 200.
PostgreSQL: How to Update Records | 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
Driving RevOps Efficiency Through AI-Driven Database Optimization with Enteros
- 21 January 2026
- Database Performance Management
Introduction Revenue Operations (RevOps) has become the backbone of modern digital enterprises. By aligning sales, marketing, finance, and customer success, RevOps promises predictable growth, faster decision-making, and improved customer lifetime value. Yet, for many organizations, RevOps efficiency remains elusive. The missing link is often hidden deep within the technology stack: the database layer. Every revenue … Continue reading “Driving RevOps Efficiency Through AI-Driven Database Optimization with Enteros”
How Retail Companies Can Reduce Cloud Costs Through Database Optimization with Enteros
Introduction Retail has become one of the most data-intensive industries in the digital economy. Modern retailers rely on cloud-powered platforms to support omnichannel commerce, real-time inventory visibility, personalized recommendations, dynamic pricing, loyalty programs, supply chain optimization, and customer analytics. At the center of all these capabilities sits a critical layer: databases. Retail databases process millions … Continue reading “How Retail Companies Can Reduce Cloud Costs Through Database Optimization with Enteros”
Database Optimization and Performance Intelligence for Real Estate SaaS Platforms with Enteros
- 20 January 2026
- Database Performance Management
Introduction Real estate SaaS platforms have become the digital backbone of the modern property ecosystem. From online listings and virtual tours to pricing intelligence, transaction management, CRM systems, property analytics, and tenant engagement platforms—nearly every real estate interaction today is powered by software. At the heart of these platforms lies one critical dependency: databases. Real … Continue reading “Database Optimization and Performance Intelligence for Real Estate SaaS Platforms with Enteros”
Smarter Cloud Spend for Financial Institutions: Enteros’ Database Performance and FinOps Intelligence
Introduction Cloud adoption has fundamentally transformed the financial services industry. Banks, fintechs, payment processors, insurers, and capital markets firms now rely on cloud platforms to deliver real-time transactions, digital banking experiences, AI-driven risk models, regulatory reporting, fraud detection, and data analytics at scale. At the center of this transformation sits one critical layer: databases. Databases … Continue reading “Smarter Cloud Spend for Financial Institutions: Enteros’ Database Performance and FinOps Intelligence”