Building Multi-Tenant RAG Applications With PostgreSQL: Choosing the Right Approach

This article discusses how to handle multi-tenancy in retrieval-augmented generation (RAG) applications built with PostgreSQL and the pgvector extension. Multi-tenancy is a design approach where multiple users or organizations share a single instance of software, ensuring data isolation and security. It offers benefits such as scalability, customization, compliance, efficient updates, cost-effectiveness, and consistent performance but also presents challenges like increased security threats, codebase complexity, backup and restoration issues, limited customization options, and potential global problems affecting all tenants simultaneously. PostgreSQL, enhanced with the pgvector extension, provides a robust solution for implementing multi-tenant RAG apps due to its built-in full-text search capabilities, JSON support, vector extensions, row-level security, scalability, ACID compliance, and extensibility. The article also highlights Timescale Cloud's open-source AI stack, which includes pgvector, pgvectorscale, and pgai, as a way to easily build and scale RAG, search, and agents applications. To implement RAG with PostgreSQL, the workflow involves ingesting and chunking data, converting text into vector embeddings using an embedding model, and storing these vectors in PostgreSQL using pgvector. When a user query is received, the system retrieves relevant information from the vector database based on similarity search, combines it with additional context, and generates a response using a large language model (LLM). The article presents four levels of multi-tenancy implementation in PostgreSQL: table-level separation, schema-level separation, logical database separation, and database service separation. Each level has its pros and cons, making them suitable for distinct use case scenarios based on shared resources, data separation, customization, scalability, and costs. By carefully considering the optimal use cases and aligning them with an application's needs, developers can create a scalable, secure, and performant RAG system in PostgreSQL.