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

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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
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