Mapping Multi-Tenancy Across Vector Databases

Approximate nearest neighbor indexes scan neighborhoods without knowing who owns a vector, forcing vector databases to resolve multi-tenancy either inside physical structures or through post-search filtering. Examining architectural trade-offs across Pinecone namespaces, Weaviate sharded tenants, Milvus partition keys, Chroma, and pgvector reveals why physical data separation is often vastly cheaper and safer than relying on metadata filters. The five-tier isolation ladder explains how to balance schema flexibility, latency, and noisy neighbors without getting lost in vendor jargon. Key sources: • Pinecone docs, *Indexing overview* (namespaces, limits, metadata), retrieved 2026-11-10. — https://docs.pinecone.io/guides/index-data/indexing-overview • Pinecone docs, *Implement multitenancy* (1 RU vs 100 RU, offboarding), retrieved 2026-11-10. — https://docs.pinecone.io/guides/index-data/implement-multitenancy • Pinecone docs, *Design for multitenancy* (anti-pattern, `$in` limit), retrieved 2026-11-10. — https://docs.pinecone.io/guides/index-data/design-for-multitenancy Episode 6520 — myweirdprompts.com/n/6520 (permanent short link: myweirdprompts.com/415069) Listen on Android: MWP FM Player — myweirdprompts.com/apk