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Indexes

As your database grows, so does the time it takes to search through your data. Whether you're filtering orders, joining customer records, or looking up log entries, performance matters—and that's where indexes come in.

In this article, we'll introduce what indexes are in PostgreSQL, why they matter, and how you can use them to make your queries faster and more efficient.

What Are Indexes in PostgreSQL?

An index is a data structure that makes it faster to find specific rows in a table—similar to the index in the back of a book. Instead of scanning the entire table, PostgreSQL uses the index to jump straight to the relevant rows.

Indexes don’t change the actual data in your table, but they create a quick reference that can significantly reduce query times, especially on large datasets.

Why Are Indexes Important?

Without indexes, PostgreSQL has to scan every row in a table to find matching results. This is fine for small datasets, but once you start dealing with thousands or millions of rows, those full table scans slow things down.

Indexes help by:

  • Reducing query response times

  • Improving performance for filtering (WHERE), sorting (ORDER BY), and joining tables

  • Supporting fast lookups on frequently queried columns

  • Enhancing performance for full-text and JSON searches (with GIN indexes)

Used correctly, indexes can speed up your application and reduce the load on your database server.

Real-World Use Cases

Indexes are widely used in all kinds of applications:

  • E-commerce: Quickly look up products by category, price range, or search term

  • Finance: Filter transactions by account or date range

  • Analytics: Speed up aggregations and time-based queries

  • CRM systems: Join large contact tables with interaction logs or campaign data

  • APIs: Improve response times for filtered or paginated results

In nearly every production system, indexes are a key part of maintaining speed and responsiveness as data scales.

What You’ll Learn in This Section

This section of the documentation will walk you through the core concepts, syntax, and best practices for using indexes in PostgreSQL. Topics include:

  • CREATE INDEX – How to create basic and custom indexes

  • B-Tree Indexes – The default and most commonly used index type

  • Hash Indexes – For fast equality searches (less commonly used)

  • GIN Indexes – For indexing JSON, arrays, and full-text search

  • GiST Indexes – For complex data types like geometric or fuzzy search

  • BRIN Indexes – For large, naturally ordered data (like time-series logs)

  • Expression Indexes – Index based on a function or expression

  • Partial Indexes – Index only a subset of rows (useful for filtering)

  • REINDEX – Rebuilding indexes when needed

  • Dropping Unused Indexes – Keeping your database lean

  • Performance Considerations – Balancing speed with storage and write performance

You’ll also learn how to use EXPLAIN to understand whether your indexes are being used effectively in your queries.