I really need to figure out which vector DB is gonna hold up best for this new RAG setup I'm building with DeepSeek V4 Pro because the performance looks insane and I dont want my database to be the bottleneck. I'm basically torn between going with Pinecone's serverless offering or just biting the bullet and setting up a Milvus cluster on my own hardware. I've also heard some crazy good things about Weaviate's hybrid search lately but I'm totally getting overwhelmed with the options.

The project is a legal-tech tool I'm trying to launch by mid-October so I'm on a super tight 4-week timeline here in NYC. We're dealing with about 2 million documents initially but it's gonna grow fast. DeepSeek V4 is super sensitive to the quality of the chunks you feed it so I need something that handles metadata filtering like a beast. I've got a budget of roughly $300 a month to start for the database hosting so I cant go too crazy with some of the enterprise-level pricing just yet.

Here is what I am looking at:

• Pinecone: Love the zero-maintenance vibe but I'm worried about the costs scaling once we hit 10M+ vectors and if the latency will kill the DeepSeek response time.
• Milvus: Seems like the gold standard for performance but man the setup looks like a headache and I dont want to spend my whole launch week debugging K8s clusters when I should be fixing the frontend.
• Qdrant: I saw some benchmarks saying it's faster for high-dimensional stuff which DeepSeek seems to prefer for its embeddings?

I'm leaning towards Pinecone just to get out the door fast but part of me feels like I'll regret not having the control of Milvus or the hybrid search capabilities of Weaviate. Does DeepSeek V4 Pro have any weird quirks with how it expects its context windows filled that would make one of these a clear winner? I really want to make sure the retrieval is pinpoint accurate because legal stuff can't have hallucinations. What are you guys seeing in production right now?...