The JusDB Database Engineering Blog

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.

Logical replication in PostgreSQL has a critical gap: slots do not survive failover. PostgreSQL 17 finally fixes this with failover slots, plus adds row and column filtering for selective replication.

Connection exhaustion is one of the most common causes of database downtime at scale. Here is how production teams use PgBouncer and ProxySQL to handle 10,000+ concurrent connections.

Diagnose and fix PostgreSQL query plan cache issues. Covers generic vs custom plans, plan_cache_mode setting, DEALLOCATE, statistics targets, and pg_stat_statements variance detection.

Master database index design: composite index column order, covering indexes with INCLUDE, partial indexes for filtered queries, functional indexes, and unused index auditing.

Explore PostgreSQL 18 revolutionary features including async I/O, improved parallelism, enhanced JSON support, and developer experience improvements coming in 2025.

Compare three PostgreSQL multi-tenant patterns: shared schema with RLS, schema-per-tenant, and database-per-tenant. Includes hash partitioning for shared schema at scale.