Designing Multi-Tenancy RAG with Milvus: Best Practices for Scalable Enterprise Knowledge Bases
Blog post from Zilliz
Retrieval-Augmented Generation (RAG) has emerged as a trusted solution for large organizations to enhance their Language Model-powered applications, especially those with diverse users. As these applications grow, implementing a multi-tenancy framework becomes essential. Multi-tenancy provides secure, isolated access to data for different user groups, ensuring user trust, meeting regulatory standards, and improving operational efficiency. Milvus is an open-source vector database built to handle high-dimensional vector data and is an indispensable infrastructure component of RAG, storing and retrieving contextual information for LLMs from external sources. Milvus offers flexible multi-tenancy strategies for various needs, including database-level, collection-level, and partition-level multi-tenancy.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| RAG | 23 | 1,581 | 239 | 69 | -19% |
| LLM | 4 | 3,081 | 500 | 165 | -9% |
| Vector Search | 4 | 4,345 | 322 | 102 | +56% |
| Kubernetes | 1 | 2,053 | 206 | 86 | +22% |
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