Database Indexing & Query Optimization Strategies for MySQL & PostgreSQL

Slow database queries are the single largest performance bottleneck in web applications. Mastering database indexing empowers engineers to handle massive datasets effortlessly.

1. How B-Tree Indexes Work

B-Tree indexes maintain sorted pointer trees on indexed columns, reducing search complexity from O(N) full table scans to O(log N) logarithmic lookups.

2. Analyzing Execution Plans with EXPLAIN

Before adding indexes, always run EXPLAIN or EXPLAIN ANALYZE on slow SQL queries to examine key utilization, scanned rows, and join algorithms.

EXPLAIN ANALYZE SELECT u.id, u.email, o.total_amount 
FROM users u 
JOIN orders o ON u.id = o.user_id 
WHERE o.status = 'completed' AND o.created_at >= '2026-01-01';

Avoiding Index Anti-Patterns

Avoid indexing low-cardinality columns (e.g. boolean flags) or applying functions on indexed columns in WHERE clauses, which invalidate index scans.

Composite indexes must follow the Leftmost Prefix Rule (filtering columns first, range condition columns last).