AWS Database Blog
Author: Frank Dallezotte
Frank Dallezotte is a Senior Solutions Architect at AWS and is passionate about working with independent software vendors to design and build scalable applications on AWS. He has experience creating software, implementing build pipelines, and deploying these solutions in the cloud.
Build an AI-powered text-to-SQL chatbot using Amazon Bedrock, Amazon MemoryDB, and Amazon RDS
Text-to-SQL can automatically transform analytical questions into executable SQL code for enhanced data accessibility and streamlined data exploration, from analyzing sales data and monitoring performance metrics to assessing customer feedback. In this post, we explore how to use Amazon Relational Database Service (Amazon RDS) for PostgreSQL and Amazon Bedrock to build a generative AI text-to-SQL chatbot application using Retrieval Augmented Generation (RAG). We’ll also see how we can use Amazon MemoryDB with vector search to provide semantic caching to further accelerate this solution.