Practice — Vector Databases and Hybrid Search (6 questions)

A team building an internal knowledge-search tool has 600,000 document chunks, expects about 25 queries/second at peak, and every query must filter to the requesting employee's department (dozens of departments, each owning a modest, roughly even slice of the corpus). They already run Postgres for the rest of the product. A senior engineer proposes Pinecone "because that's what everyone uses for RAG."

1. Would you recommend pgvector or a dedicated vector database here, and why?
2. Which single input, if changed enough, would flip your recommendation, and to what new value?
3. What operational cost is the team implicitly signing up for if they adopt a dedicated vector database at this scale?