Preamble
PostgreSQL index: You will learn how to create, delete, and rename indexes in PostgreSQL with syntax and examples.
What is PostgreSQL index?
An index is a performance tuning method that allows you to extract records more quickly. An index creates a record for each value that appears in the indexed columns.
Create an index
You can create an index in PostgreSQL using the CREATE INDEX operator.
The syntax for the CREATE INDEX operator in PostgreSQL
CREATE [UNIQUE] INDEX [CONCURRENTLY] index_name
[ USING BTREE | HASH | GIST | SPGIST | GIN ]
ON table_name
(index_col1 [ASC | DESC],
index_col2 [ASC | DESC],
…
index_col_n [ASC | DESC]);
- UNIQUE – Optional. The UNIQUE modifier indicates that the combination of values in indexed columns must be unique.
- CONCURRENTLY – Optional. When an index is created, it will not lock the table. By default, the table is locked when an index is created.
- index_name – The name to be assigned to an index.
- table_name – The name of the table where the index is created.
- index_col1, index_col2,… index_col_n – Columns for use in an index.
- ASC – Optional. The index is sorted in ascending order for this column.
- DESC – Optional. The index is sorted in descending order for this column.
Let’s look at an example of how to create an index in PostgreSQL.
For example:
CREATE INDEX order_details_idx
ON order_details (order_date);
In this example, the CREATE INDEX operator will create an index with the name order_details_idx, which consists of the order_date field.
UNIQUE INDEX
To create a unique index for a table, you must specify the UNIQUE keyword when creating the index.
For example:
CREATE UNIQUE INDEX order_details_idx
ON order_details (order_date, note);
In this example, we have created a unique index for the order_details table, which consists of the order_date and note fields, so that the combination of these fields must always contain a unique value without duplicates.
This is a great way to ensure the integrity of your database if you require unique values in columns that are not part of your primary key.
Drop Index
You can remove an index in PostgreSQL using the DROP INDEX operator.
The syntax for removing an index using the DROP INDEX operator in PostgreSQL
DROP INDEX [CONCURRENTLY] [IF EXISTS] index_name
[ CASCADE | ];
- CONCURRENTLY – Optional. When an index is deleted, it does not block the table. By default, the table is locked while the index is removed from the table.
- IF EXISTS – Optional. If specified, the DROP INDEX operator will not cause an error if no index exists.
- index_name – The name of the index to be deleted.
- CASCADE – Optional. All objects that depend on this index are also deleted.
- RESTRICT – Optional. The index will not be deleted if there are objects that depend on the index.
Let’s look at an example of how to remove an index in PostgreSQL.
For example:
DROP INDEX order_details_idx;
In this example, we removed an index with the name website_idx from the site’s table.
Rename the index
You can rename an index into PostgreSQL using the ALTER INDEX operator.
The syntax for renaming an index using the ALTER INDEX operator
ALTER INDEX [IF EXISTS] index_name,
RENAME TO new_index_name;
- IF EXISTS – Optional. If specified, the ALTER INDEX operator will not cause an error if no index exists.
- index_name – The name of the index that you want to rename.
- new_index_name – The new name for an index.
Let’s look at an example of how to rename an index in PostgreSQL.
For example:
ALTER INDEX order_details_idx
RENAME TO od_new_index;
In this example, we renamed the index with the name order_details_idx to od_new_index.
PostgreSQL Indexing: How, why, and when
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
Scaling AI Without Overspend: How Enteros Brings Financial Clarity to AI Platforms
- 22 January 2026
- Database Performance Management
Introduction Artificial intelligence is no longer experimental. Across industries, AI platforms now power core business functions—recommendation engines, fraud detection, predictive analytics, conversational interfaces, autonomous decision systems, and generative AI applications. But as AI adoption accelerates, a critical problem is emerging just as fast: AI is expensive—and most organizations don’t fully understand why. Read more”Indian Country” … Continue reading “Scaling AI Without Overspend: How Enteros Brings Financial Clarity to AI Platforms”
AI-Native Database Performance Management for Real Estate Technology Enterprises with Enteros
Introduction Real estate has rapidly evolved into a technology-driven industry. From digital property marketplaces and listing platforms to smart building systems, valuation engines, CRM platforms, and AI-powered analytics, modern real estate enterprises run on data-intensive technology stacks. At the center of this transformation lies a critical foundation: databases. Every property search, pricing update, lease transaction, … Continue reading “AI-Native Database Performance Management for Real Estate Technology Enterprises with Enteros”
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”