PostgreSQL Database Optimization

To get the best performance from PostgreSQL in production, you need to look at indexes, statistics, configuration, and SQL patterns. Here is a concise checklist.

1. Indexes

• Add B-tree indexes on columns used in WHERE, JOIN, ORDER BY, GROUP BY.
• Avoid redundant indexes (e.g. if you have (a, b), a separate (a) may be unnecessary).
• Use expression indexes for conditions like WHERE lower(email) = ? and partial indexes when only a subset of rows is queried.

2. Statistics and execution plans

• Run ANALYZE (or rely on autovacuum) so the planner has up-to-date statistics; after bulk loads, run ANALYZE manually.
• Use EXPLAIN (ANALYZE, BUFFERS) to see actual timing, buffer hits, and sequential vs index scans; watch for bad row estimates.

3. Configuration

• Memory: shared_buffers (e.g. ~25% of RAM), work_mem (for sorts/hashes), maintenance_work_mem (VACUUM, CREATE INDEX).
• Checkpoints and WAL: checkpoint_completion_target, wal_buffers, max_wal_size.
• Connections: Keep max_connections reasonable; use a connection pool (e.g. PgBouncer) to avoid exhausting memory.

4. Maintenance and monitoring

• VACUUM: Reclaim dead tuples and update visibility; tune autovacuum for busy tables.
• Monitoring: Slow queries, lock waits, replication lag, table bloat; use pg_stat_statements, pg_stat_user_tables where useful.

5. SQL and architecture

• Avoid SELECT *; fetch only needed columns.
• For large offsets, prefer keyset/cursor pagination over LIMIT n OFFSET m.
• Use read replicas and application caching for read-heavy workloads.

For full reference, see the PostgreSQL documentation (performance tips, parallel query, routine maintenance).