Why pgvector over a dedicated vector database

Every RAG tutorial reaches for a dedicated vector database on day one. For most projects that is premature. If your data already lives in Postgres, pgvector lets you add similarity search without standing up and operating a second system.

When Postgres is enough

• One database to back up, monitor, and reason about.
• Joins between your vectors and your real data, in one query.
• Transactions across both, so writes stay consistent.

When to graduate

You outgrow it when your index no longer fits comfortably in memory, or when query latency under load stops meeting your target. At that point a dedicated store earns its operational cost. Until then, the simpler system wins.