11/ TL;DR:
Vectors + relational data together, small/medium scale β pgvector.
Pure, massive-scale vector search β dedicated DB.
If this helped, an RT on the first tweet means a lot π
#pgvector#PostgreSQL#VectorDatabase#RAG#AI#LLM#devs
1/ Your project needs vector search β but which database?
A dedicated vector DB (Pinecone & co.) or just the PostgreSQL you already run, with pgvector?
A clear decision guide π§΅π
10/ There's a middle ground too:
Extensions like pgvectorscale push pgvector closer to dedicated DBs β staying in Postgres while going bigger.
Practical advice: start with pgvector. Migrate if you outgrow Postgres. Don't optimize too early.
TL;DR: CLI runs it, MCP connects it, a direct API codes it, a browser clicks it. The agent's environment and your safety needs decide which. Give it the right channel plus clear docs, and the workflow becomes repeatable and reliable.