Vector indexes are algorithms that organize vectors into searchable structures for fast similarity search, while vector databases are complete systems that wrap indexes with distributed storage, metadata filtering, persistence, and concurrent access. An autonomous driving company initially used FAISS but faced scalability issues with hundreds of thousands of isolated index files when searching across massive driving footage. Migrating to Milvus provided unified queries with metadata filters, organized collections, and 30% cost reduction while handling tens of billions of vectors in production.

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