Why Indexes Sometimes Make Queries Slower

Indexes are often seen as the ultimate solution to slow SQL queries. While they usually improve performance, there are situations where indexes can actually make queries slower.

Understanding when and why this happens is critical for building fast and scalable databases.

In this article, we’ll explore why indexes sometimes hurt performance and how to avoid common mistakes.

How Indexes Are Supposed to Help

Indexes allow the database to quickly locate rows without scanning the entire table.

In general, indexes help when:

  • Tables are large
  • Queries filter on selective columns
  • Indexes are well maintained

But this is not always the case.

Reason 1: Low Selectivity Indexes

An index on a column with very few unique values is often useless.

Example

CREATE INDEX idx_users_active ON users(active);

If most rows have active = true, PostgreSQL may choose a sequential scan instead of the index.

In some cases, forcing index usage adds unnecessary overhead.

Reason 2: Small Tables

Indexes have a cost. For small tables, scanning the whole table can be faster than using an index.

PostgreSQL is smart enough to avoid indexes when they don’t help — but unnecessary indexes still consume memory and slow writes.

Reason 3: Too Many Indexes

Each index must be updated on INSERT, UPDATE, and DELETE.

Too many indexes lead to:

  • Slower writes
  • Higher disk usage
  • Longer maintenance operations

More indexes ≠ better performance.

Reason 4: Indexes That Don’t Match the Query

Indexes must match how queries are written.

Example

CREATE INDEX idx_orders_created_at ON orders(created_at);

This index won’t help the following query:

SELECT * FROM orders WHERE DATE(created_at) = '2026-01-01';

Because the column is wrapped in a function, PostgreSQL can’t use the index efficiently.

Better Query

SELECT * FROM orders
WHERE created_at >= '2026-01-01'
AND created_at < '2026-01-02';

Reason 5: Outdated Statistics

PostgreSQL relies on statistics to decide whether to use an index.

If statistics are outdated, the query planner may choose a poor execution plan.

Solution

ANALYZE;

This helps PostgreSQL make better decisions.

Reason 6: Index Bloat

Over time, indexes can become bloated due to updates and deletes.

Bloated indexes:

  • Consume more disk space
  • Increase I/O
  • Slow down scans

Solution

  • Use VACUUM
  • Rebuild indexes when needed

How to Know If an Index Is Helping

The only reliable way is to measure.

Use EXPLAIN ANALYZE

EXPLAIN ANALYZE
SELECT * FROM orders WHERE user_id = 42;

Check whether the index is used and how much time it saves.

Best Practices for Using Indexes

  • Create indexes for real queries, not assumptions
  • Avoid indexing low-selectivity columns
  • Remove unused indexes
  • Monitor performance regularly

Conclusion

Indexes are powerful, but they are not magic.

When used incorrectly, indexes can slow down queries, waste resources, and complicate maintenance.

The key to performance is not adding more indexes — it’s understanding how your queries actually work.

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