Multi-Tenant RAG With PostgreSQL and pgvector

Multi-tenant RAG systems using PostgreSQL and pgvector must balance strict tenant isolation with reliable semantic retrieval, keeping embeddings, document metadata, and authorization controls in a shared relational database while preventing cross-tenant context exposure. A recommended design uses separate documents and chunks tables linked by composite foreign keys, PostgreSQL row-level security enforced with FORCE ROW LEVEL SECURITY, and a transaction-local tenant identifier derived from authenticated backend requests rather than client input. Backup operations require a dedicated BYPASSRLS role to ensure complete dumps, while opaque surrogate keys and careful policy design help reduce RLS-related inference risks. Retrieval performance under tenant filters depends on matching the indexing approach to tenant size and stability, using btree indexes for small slices, partial vector indexes for a few predictable tenants, partitioning or separate tables for isolated approximate indexes, and iterative scans when a shared HNSW index must return enough filtered results. To limit noisy-neighbor effects, the architecture separates synchronous retrieval from asynchronous chunking and embedding workers, uses connection pooling and per-tenant quotas, and places database, API, workers, and rate-limit infrastructure on a private network. Organizations needing physical rather than logical isolation can migrate large enterprise tenants into dedicated stacks through infrastructure-as-code, using tenant-scoped exports or logical replication.

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