Amazon Bedrock Knowledge Bases now supports Amazon OpenSearch Managed . . . Amazon Bedrock Knowledge Bases’ native integration with vector databases allows you to mitigate the need to build custom data source integrations With this launch, you can use OpenSearch managed cluster as the vector database to take advantage of the suite of features available in Bedrock Knowledge Bases
Vector store options for Bedrock Knowledgebase | AWS re:Post Unfortunately, your options for vector stores with Amazon Bedrock Knowledge Bases are indeed limited, and using a standard RDS PostgreSQL with pgvector or a managed OpenSearch instance is not currently supported
Prerequisites for using a vector store you created for a knowledge base . . . To store the vector embeddings that your documents are converted to, you use a vector store Amazon Bedrock Knowledge Bases supports a quick-create flow for some of the vector stores, so if you prefer for Amazon Bedrock to automatically create a vector index for you in one of those vector stores, skip this prerequisite and proceed to Create a knowledge base by connecting to a data source in
Amazon Bedrock now integrates with Amazon OpenSearch Service for vector . . . Here’s the translation to American English: — Amazon Bedrock Knowledge Bases has taken a significant step in its evolution by adding support for managed clusters of Amazon OpenSearch Service This update strengthens its role as a fully managed Retrieval-Augmented Generation (RAG) solution that aligns with current market needs
Improve search results for AI using Amazon OpenSearch Service as a . . . An API call will synchronize your data source with OpenSearch Serverless vector store The Amazon Bedrock retrieve_and_generate () runtime API call makes it straightforward for you to implement RAG with Amazon Bedrock and your OpenSearch Serverless knowledge base
Amazon Bedrock Knowledge Bases now supports Amazon OpenSearch Service . . . Amazon Bedrock Knowledge Bases has expanded its vector store options by adding support for Amazon OpenSearch Service Managed Clusters This enhancement provides more flexibility for storing and retrieving vector embeddings in AI applications