Database Insights

Master pg_stat_statements for PostgreSQL query analysis. Find top queries by total time, detect plan instability via stddev, identify I/O-heavy queries, and track WAL generation.

Right-size your PostgreSQL connection pool using the (cores*2)+1 formula. PgBouncer configuration, per-user limits, pool saturation monitoring, and transaction mode pitfalls.

PostgreSQL 17 ships eager freezing and improved autovacuum prioritization, the most significant vacuum improvements in a decade. Learn how to tune autovacuum for high-write tables and prevent transaction ID wraparound.

Guide the PostgreSQL query planner with enable_xxx settings, pg_hint_plan extension, and extended statistics for correlated columns. Fix bad plans without rewriting queries.

Use pgbench to benchmark PostgreSQL before and after configuration changes. Covers scale factor selection, TPC-B and read-only workloads, custom SQL scripts, and latency percentiles.

Use pg_repack to reclaim PostgreSQL table bloat without the exclusive lock of VACUUM FULL. Covers installation, table vs index repack, disk space requirements, and throttling.

When your events table hits 800 million rows, PostgreSQL declarative partitioning becomes essential. Learn range and hash partitioning, automated management with pg_partman, and zero-downtime archival.

Enable and tune PostgreSQL parallel query for analytical workloads. Covers max_parallel_workers settings, PARALLEL SAFE functions, JIT compilation, and execution plan verification.

Choose jsonb over json for PostgreSQL: GIN indexing, containment operators, path queries, and update operations with || and jsonb_set. Includes performance comparison.

Supabase, PlanetScale, and Neon each take a different approach to serverless databases. Compare their connection limits, branching features, cost models, and which fits your workload.

Implement PostgreSQL full-text search with tsvector columns, GIN indexes, and ts_rank scoring. Covers phrase search, weighted fields, and ts_headline snippets.

DuckDB brings OLAP query performance to your Python process without a server or cluster. Learn how to query Parquet files, replace heavy ETL jobs, and run analytics directly against PostgreSQL.