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Citus is a Postgres extension that spreads tables across worker nodes while the cluster still looks like a single Postgres server to your application. The coordinator intercepts query planning and distributes the work. Picking the distribution key is the decision that matters most, since every later query inherits its consequences.
The PostgreSQL 17 optimisations that change real query plans sit in the planner and executor, so existing SQL benefits untouched. SAOP scans fold an IN list into a single index pass, worth 30 to 50 percent off p99 latency for 20 to 100 IDs. Streaming I/O cuts cold sequential scans and ANALYZE by 15 to 40 percent.
PostgreSQL 16 closes the historical gaps in logical replication: parallel apply near 2x faster, logical slots served from physical standbys, and the scaffolding for bidirectional replication. The result is a first-line tool for cross-version migrations and CDC pipelines.
This guide installs PostgreSQL 16 with pgvector on Debian or Ubuntu using the official PGDG repository, creates a dedicated role and database, tunes memory for production, and explains when the HNSW index beats IVFFlat depending on vector volume and the available maintenance window.
pgvector matured in 2023-2024 with the HNSW index type and parallel construction that arrived in version 0.6. For projects already running PostgreSQL, a dedicated vector database is not needed in most cases: this guide explains when PostgreSQL is enough, how to configure the index, and where it starts to fall short.
PostgreSQL 16, released in September 2023, adds logical replication from a standby, the pg_stat_io view for breaking down I/O by operation type and context, and parallel FULL OUTER JOIN support. Upgrading from 15 is straightforward; 13 loses support in November 2025, so plan the update soon.
pgvector turns PostgreSQL into a fully functional vector database without adding a separate service to the stack. It extends Postgres with the vector type, IVFFlat indexes for approximate nearest-neighbour search (ANN), and the ability to combine relational SQL filters with vector ranking in a single query. For most RAG projects and internal chatbots, those limits never become a problem.
