PostgreSQL

• Richer types (arrays, JSONB, XML, custom types); extensible via PostGIS (geospatial) and many extensions. • Excels at complex queries and write-heavy workloads; stronger query optimizer and index types. • Requires manual vacuuming for dead tuples and index bloat management. • Logical replication, improving but more complex to configure. • A resident server process coordinating access over connections — built to be a shared repository for many clients across a network. • MVCC: readers never block writers and many writers proceed concurrently — the reason it's the default for multi-user server applications. • A real server: connection pooling, autovacuum tuning, replication, point-in-time recovery, major-version upgrades — or you offload that to a managed provider. • No single-file constraint; read replicas, partitioning, and sharding (or managed offerings) take it to enterprise scale. • The richest extension ecosystem in open-source RDBMSs — PostGIS (geospatial), pgvector (AI embedding search), TimescaleDB — making it the default backend for AI apps in 2026. • Relational tables with enforced types, foreign keys, and migrations. Best when structure is stable and integrity matters. (Techplained, 2025) • Full SQL: joins, window functions, CTEs, and extensions like PostGIS/timescaledb make it the strongest for reporting and analytics. (Builder.ai2sql, 2026) • Scales via read replicas and partitioning; true horizontal sharding needs an extension like Citus. Single-node performance is excellent. (Atomnyx, 2026) • Decades-mature ACID with SERIALIZABLE isolation — the default for money and ERP systems. (Tech Insider, 2026)