In collaboration with

Retrieval Augmented Generation (RAG) grounds your model in your data, not its training set. Agentic memory carries context across sessions. Semantic search matches intent, not keywords.

Each depends on the same building block: a vector database. Explore what to evaluate for your use case:

• Architecture diagrams: Each pattern mapped with Amazon Bedrock and Amazon Bedrock AgentCore
• Evaluation framework: Hybrid search, scaling, hosting trade-offs, embedding pipeline fit, and metadata filtering
• Free trials: Test vector databases in AWS Marketplace and start building

Get the guide and find the right vector database for your stack.

Download the evaluation guide ›

About AWS Marketplace:

Visit AWS Marketplace for help finding the best solutions for your use case and add new capabilities to your tech stack with your AWS account:

• Tools are designed to plug in to your AWS workflows and integrate with your favorite AWS services
• Evaluate fast with free trials and developer-tier pricing to support fast prototyping
• Avoid upfront license fees and pay only for what you use, consolidating billing with your AWS account
• A broad selection of tools across AI, data, observability, security and more can enhance how you build with AWS