Databases often become performance bottlenecks even when application code is well-optimized. This guide covers diagnosing DB slowdowns using query profiling (EXPLAIN ANALYZE, slow query logs) and key metrics, then addresses fixes at two levels: query optimization (proper indexing, avoiding SELECT *, using JOINs over nested queries) and architectural improvements (schema normalization vs. denormalization, caching with Redis/Memcached, connection pooling with pgbouncer, materialized views, sharding/partitioning, and read replicas). The core advice is to profile first, then apply targeted optimizations rather than guessing.
Table of contents
Why the Database Can Become a Bottleneck?Diagnosing the ProblemOptimizing Your QueriesScaling Beyond Queries: Architectural OptimizationsConclusion: Diagnose Before You Optimize1 Comment
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