pgvector vs Weaviate

pgvector adds vectors to Postgres; Weaviate is an AI-native vector database with managed cloud and BYOC options. The decision is whether you want vectors in your existing operational database or in a purpose-built engine with deeper AI tooling.

Where pgvector wins

• One database, one backup, one auth story. ACID transactions span vector and relational writes. Joins enrich vector results in a single query.

• Row-level security for free multi-tenancy. Weaviate's tenant-per-collection model is more sophisticated, but pgvector's RLS enforcement is harder to bypass.

• No new vendor or operational surface. Postgres is already in most stacks. Weaviate adds a service to run.

Where Weaviate wins

• Generative modules run RAG inside the database. generative-* retrieves + calls an LLM in one query. pgvector returns rows; you orchestrate generation in app code.

• Tenant-per-collection scales to 100k+ tenants with offloading. First-class per-tenant lifecycle that Postgres schemas don't match.

• Built-in vectorizer modules. OpenAI, Cohere, Voyage, Hugging Face, Ollama at ingest time. pgvector stores vectors but generates none.

• First-party MCP server. pgvector relies on community wrappers.

The agentic difference

For agents that already read and write Postgres data, pgvector keeps everything in one transactional store with RLS-enforced isolation. For agents with many long-tail per-user vector spaces or where you want retrieval + generation inside the database, Weaviate's tenant model and generative modules pull ahead. Weaviate's first-party MCP server simplifies agent integration today.

When to pick which

• Pick pgvector when Postgres is already the operational store and you want vectors inside the same database.

• Pick Weaviate when you need first-class multi-tenancy at scale, generative modules, built-in vectorizers, or a first-party MCP server.