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Retrieval-augmented generation (RAG) allows you to build GenAI applications that use your own data, to optimize LLM performance.
Join our AMA to ask us about RAG, vector databases, running RAG...
EricStarker
Updated Feb 14, 2024
gyangupta
Feb 14, 2024Copper Contributor
What are the different Vector Databases available in the Azure platform?
- TyBeckerFeb 14, 2024
Microsoft
(in no particular order) 1. Azure Postgres Flexible Server (it has pgvector and azure_openai extensions to support) 2. Azure Cosmos DB Postgres and Mongo vCore 3. Azure AI Search (has robust semantic search that can be used in conjunction with vector search, unless your data already exists in one of the above databases this is the most common use pattern) - gyanguptaFeb 14, 2024Copper ContributorAlong with LLM model size, what is the limitation for Vector DB size to get optimal performance?
- gia_mondragonFeb 14, 2024
Microsoft
The vector size limits in AI Search can be found here: https://learn.microsoft.com/en-us/azure/search/vector-search-index-size. Limits are set based not only on technical limitations (depending on the limit) but also based on performance testing. However, to obtain optimal retrieval performance from your RAG app, you can take a look at best practices listed here: https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/azure-ai-search-outperforming-vector-search-with-hybrid/ba-p/3929167