This blog was first authored in 2020. We’ve updated it in 2025 for clarity and relevance, reflecting current practices while honoring their original perspective.

PostgreSQL offers a rich set of indexing features, and while there’s no shortage of articles explaining how indexes work, one challenge often goes overlooked: maintenance. Over time, unused or duplicate indexes can pile up, slowing down inserts and updates, bloating storage, and making your environment harder to manage.

This post highlights practical queries you can run to check the health of your indexes. These are especially useful when cleaning up old schemas, tuning performance, or troubleshooting sluggish workloads.

Why PostgreSQL index maintenance matters

Indexes are critical for query performance and for enforcing uniqueness. But every index adds overhead: each insert, update, or delete has to keep those indexes in sync. Left unchecked, unnecessary indexes can hurt rather than help. That’s why it’s important to periodically review them, remove duplicates, and track usage.

The queries below show how to:

  • List indexes on a table 
  • Check if they are unique 
  • Measure their size 
  • Compare table and index storage 
  • Rebuild bloated indexes 
  • Spot unused or duplicate indexes 

1. List indexes on a table

Use this query to see all indexes on a given table, along with the schema-qualified table name.

2. Check index uniqueness

Unique indexes enforce constraints at the database level. The indisunique column in pg_index tells you if an index is unique.

3. Find the size of an index

A quick way to see how much space an index is using:

4. Compare table size with indexes

This query shows the table size, its indexes, and the total storage consumed. It’s an easy way to spot when indexes are taking up more space than expected.

  • pg_relation_size: returns size of a table or index
  • pg_total_relation_size: includes table + indexes

5. Show the index creation query

Need to see how an index was created? Use pg_get_indexdef:

6. Rebuild bloated indexes without downtime

If an index becomes corrupted or bloated, REINDEX CONCURRENTLY lets you rebuild it while keeping the table available.

7. Check supported data types for index methods

Not every index method supports every operator or data type. This query shows which data types are supported by B-tree.

8. Find unused indexes

Indexes with idx_scan counts close to zero may be unnecessary. Be careful before dropping them — some may enforce uniqueness even if rarely scanned.

9. Detect duplicate indexes

Duplicate indexes waste space and hurt performance. This query helps you spot them.

Conclusion

PostgreSQL’s catalog tables give you a powerful way to monitor, analyze, and manage indexes. With queries like these, you can stay ahead of bloat, enforce best practices, and keep performance steady as your workloads grow.

Maintaining PostgreSQL index queries is just one piece of running PostgreSQL at scale. The bigger challenge is making the right choices up front: how you deploy, whether you use open source or proprietary add-ons, and how you balance cost with enterprise-grade features.

If you’re weighing your options, don’t go in without the information you need. Learn from IT leaders who have already been through the process;  download our Enterprise PostgreSQL Buyer’s Guide: 10 Hard-Earned Lessons from IT Leaders Who’ve Been There Before.

 

Subscribe
Notify of
guest

0 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments