How to Choose the Right Vector Database for a Production-Ready RAG Chatbot

Building production-ready RAG chatbots faces a critical challenge: choosing vector databases that handle both semantic search and numerical filtering for real customer queries like "show me laptops under $500" or policy questions with specific constraints. After evaluating ChromaDB, Pinecone, Milvus, and Weaviate, Weaviate emerged as the optimal choice due to its intuitive API, native filtering during search, flexible deployment options, and ability to scale while maintaining clean query syntax that junior developers can master quickly.