Amazon Bedrock Knowledge Bases
Amazon Bedrock Knowledge Bases: A deep, AWS-centered toolkit for production RAG over enterprise and structured data. Ranked #1 of 26 in Retrieval-Augmented Generation Tools by our editors (9.3/10); pricing: Paid; best for AWS-centric production RAG deployments.
At a glance
- Editor score9.3 / 10
- PricingPaid
- Best forAWS-centric production RAG deployments
- Source citationsYes
- Founded2023
- Facts checked22 Sep 2026
Where it wins
- Hybrid search, reranking, citations, and agentic retrieval
- Broad connectors across AWS, SaaS, databases, and vector stores
- Supports multimodal documents and natural-language-to-SQL generation
Where it doesn't
- Cloud deployment limits teams seeking non-cloud options
- Usage-based billing spans multiple retrieval and AWS components
- Its breadth may be more than needed for narrowly scoped RAG projects
Our verdict on Amazon Bedrock Knowledge Bases
Amazon Bedrock Knowledge Bases is a managed Retrieval-Augmented Generation service for developers and organizations building AI applications and agents over proprietary data. It handles document ingestion and chunking, generates and stores vector embeddings, retrieves relevant content, and can produce answers with source citations. The service is aimed at teams building production AI experiences that need enterprise data access, rather than users looking for a standalone document-chat application.
Its strongest differentiator is retrieval depth. Semantic and hybrid search can be combined with result reranking, while agentic retrieval supports multi-step queries. Multimodal document processing extends beyond conventional text handling, and structured-data retrieval adds natural-language-to-SQL generation through Amazon Redshift and AWS Glue Data Catalog. This makes the product suitable for applications that need to combine unstructured documents with structured business data and more advanced retrieval workflows.
The ecosystem is particularly well suited to AWS-centered architectures. Connectors include Amazon S3, Confluence, Google Drive, Microsoft OneDrive, Microsoft SharePoint, and a web crawler, while supported data and retrieval destinations include Amazon OpenSearch Serverless, Amazon OpenSearch Service Managed Clusters, Amazon Neptune, Amazon Aurora, Pinecone, Redis Enterprise Cloud, and MongoDB Atlas. Teams already operating across these services can assemble a broad retrieval layer without narrowing their data sources to one repository. The trade-off is cloud-only deployment and usage-based billing across retrieval, ingestion, embeddings, reranking, foundation models, and related AWS resources. Choose it for sophisticated, AWS-oriented RAG applications; a narrower tool may suit teams with simpler retrieval needs or non-cloud deployment requirements.
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Amazon Bedrock Knowledge Bases pricing
Amazon Bedrock Knowledge Bases fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Not verified |
| Source citations | Yes |
| Hybrid search | Yes |
| Result reranking | Yes |
| Source connectors | Not verified |
| Deployment | Cloud |
| RAG workflow builder | Not verified |
| Maximum file size | 50 MB |
| Deployment | Cloud |
| Platforms | Web |
| Support | Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 16 integrations: Amazon S3, Confluence, Google Drive, Microsoft OneDrive, Microsoft SharePoint, Web Crawler … |
| Pricing | Paid (source) |
| Website | aws.amazon.com |
| Facts checked | 22 Sep 2026 |
Amazon Bedrock Knowledge Bases integrations
Amazon Bedrock Knowledge Bases lists 16 integrations on its own site.
- Amazon S3
- Confluence
- Google Drive
- Microsoft OneDrive
- Microsoft SharePoint
- Web Crawler
- Amazon Redshift
- AWS Glue Data Catalog
- Amazon OpenSearch Serverless
- Amazon OpenSearch Service Managed Clusters
- Amazon Neptune
- Amazon Aurora
- Pinecone
- Redis Enterprise Cloud
- MongoDB Atlas
- Amazon S3 Vectors
Alternatives to Amazon Bedrock Knowledge Bases
- HaystackA modular Python framework for customizable RAG pipelines, agents, and semantic search.9.2
- LangChainA flexible foundation for developers building programmable RAG and agent applications.9.1
- RAGFlowDeep-document RAG with hybrid retrieval, citations, workflows, and self-hosting.8.8
See all Amazon Bedrock Knowledge Bases alternatives →
Amazon Bedrock Knowledge Bases vs the competition
- Amazon Bedrock Knowledge Bases vs Haystack
- Amazon Bedrock Knowledge Bases vs LangChain
- Amazon Bedrock Knowledge Bases vs RAGFlow
- Amazon Bedrock Knowledge Bases vs Progress Agentic RAG
- Amazon Bedrock Knowledge Bases vs Haystack Enterprise Platform
- Amazon Bedrock Knowledge Bases vs Vectara
Compare Amazon Bedrock Knowledge Bases with any tool side by side →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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