A generative AI use case using Amazon RDS for SQL Server as a vector data store

This article discusses how to use Amazon RDS for SQL Server as a vector data store for implementing a generative AI use case involving similarity search with retrieval augmented generation (RAG).

Specifically, the article covers:

• An overview of generative AI, foundation models, and RAG
• Benefits of using Amazon RDS for SQL Server as a vector data store
• The solution architecture involving RDS for SQL Server, SageMaker, and Amazon Bedrock
• Steps to set up the solution using RDS for SQL Server, Bedrock, and a SageMaker notebook
• Examples of running similarity searches by vectorizing user prompts, querying the vector data store, and retrieving relevant results
• Conclusion and clean-up steps