PostgreSQL is remarkably capable out of the box, but there are a handful of patterns that separate a fast database from a slow one.
Index what you query, not what you think you’ll query
Indices are only useful if the query planner uses them. Run EXPLAIN ANALYZE on your slow queries before adding indices — you might find the index already exists but isn’t being used because of a type mismatch or a function wrapping the column.
Avoid SELECT * in production code
Fetching every column when you need three wastes memory and network bandwidth. It also breaks query caching. Be explicit about the columns you need.
Use connection pooling
Opening a new database connection for every request is expensive. Use PgBouncer or a library-level pooler like pg-pool. This single change can dramatically improve throughput for high-traffic applications.
Partial indices are underrated
If you frequently query a subset of rows (e.g., WHERE status = 'active'), a partial index on that condition is far smaller and faster than a full-table index.
VACUUM is your friend
PostgreSQL’s MVCC architecture means dead rows accumulate. Autovacuum handles most cases, but for tables with heavy write loads, tune autovacuum aggressively or run manual VACUUM ANALYZE after large data operations.
Measure before you optimise
The most important advice: profile first. Slow applications usually have one or two problem queries responsible for 80% of the latency. Find those before touching anything else.