Database Performance Optimization: A Practical Content Strategy for Engineering Teams

Most database performance problems aren't database problems — they're query problems, index problems, or architecture problems that manifest as database slowdowns. Here's how to build a systematic approach to database performance. The Performance Investigation Stack Before optimizing anything, understand where time is actually being spent: Application Layer ORM-generated queries (N+1 problem) Missing connection pooling Unnecessary round trips Query Layer Full table scans Missing indexes Inefficient JOINs Unoptimized LIKE patterns Infrastructure Layer Disk I/O contention Memory pressure Network latency CPU saturation Query Optimization Fundamentals Reading Query Plans PostgreSQL: EXPLAIN ANALYZE MySQL: EXPLAIN MongoDB: explain() Look for: Seq Scan (usually bad — full table scan) Nested Loop on large datasets (can be expensive) High actual vs estimated rows (statistics problem) High execution time in EXPLAIN ANALYZE output Index Strategy Not all indexes are created equal. B-tree indexes