pinecone

Managed, serverless vector DB for production AI. Hybrid search, low latency (<100ms p95).

• Managed vector database for AI applications
• Supports dense and sparse vector search
• Provides metadata filtering and namespaces
• Fully automated with auto-scaling

• Fully managed SaaS platform
• Auto-scales to billions of vectors
• p95 latency <100ms
• 99.9% uptime SLA
• Hybrid search (dense + sparse)
• Metadata filtering with $eq, $gte, $in, $and, $or
• Namespaces for data partitioning
• Serverless and self-hosted alternatives exist

1. 1.Install pinecone-client via pip
2. 2.Create index with specified dimension, metric, and spec
3. 3.Upsert vectors with metadata and sparse values
4. 4.Query with top_k, filters, and namespaces
5. 5.Use in RAG, recommendation systems, or semantic search