Database Indexing Strategies for High-Traffic Applications

Poor indexing is the number one cause of slow database queries. Here is how to get it right.

Understanding Index Types

B-Tree Indexes

The default index type in most databases. Excellent for equality and range queries, ORDER BY, and JOIN operations.

Hash Indexes

Faster for exact equality lookups but cannot handle range queries. Use sparingly.

GIN / GiST Indexes

Specialized for full-text search, JSON queries, and geometric data in PostgreSQL.

Composite Indexes

The order of columns matters. An index on (user_id, created_at) supports:

• Queries filtering by user_id alone
• Queries filtering by user_id AND created_at
• Queries filtering by user_id with ORDER BY created_at

It does NOT support queries filtering only by created_at.

The EXPLAIN Command

Always validate your indexes:

EXPLAIN ANALYZE
SELECT * FROM orders
WHERE user_id = 123
ORDER BY created_at DESC
LIMIT 10;

Look for "Seq Scan" (sequential scan) on large tables — that is a sign you need an index.

Common Mistakes

1. Over-indexing: Each index adds write overhead. Only index columns used in WHERE, JOIN, and ORDER BY.
2. Ignoring covering indexes: Include all selected columns to avoid table lookups.
3. Not monitoring unused indexes: Remove indexes that are never read.