Amazon Bedrock Knowledge Bases vs RAGFlow
No clear leader: Amazon Bedrock Knowledge Bases (58.2) and RAGFlow (53.5) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for rag tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Amazon Bedrock Knowledge Bases
Amazon Bedrock Knowledge Bases automates linking AI models to your organization's data, from extracting and indexing documents to executing intelligent searches that provide models with current, relevant context.
RAGFlow
RAGFlow is an open-source RAG engine that streamlines data processing and integration for building production-ready AI systems. It supports multiple data formats and provides configurable LLM and embedding options with agent-based workflows.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Amazon Bedrock Knowledge Bases
Usage-based pricing: free multimodal parsing, $1.00 per 1,000 Agentic Retrieve API calls, $0.010 per processed page
- Standard TierFree parsing, $1.00 per 1,000 Agentic API calls, $0.010 per page processed
- Multimodal document parsing
- Embeddings generation
- Standard retrieval API
- Agentic multi-step retrieval
- Native connectors to S3, SharePoint, Confluence, OneDrive, Google Drive
- +2 more
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- Confluence
- Google Drive
- S3
Amazon Bedrock Knowledge Bases
- Amazon S3
- SharePoint
- OneDrive
- Web crawlers
- Amazon Bedrock AgentCore
- Asana
- LangChain
- Strands
- Bedrock Data Automation
- Web Crawler
RAGFlow
- Discord
- Feishu
- Telegram
- Line
- Notion
- OpenAI
- DeepSeek
- Gemini
- OpenClaw
- OpenAI GPT-5
- Google Gemini 3 Pro
- DeepSeek v4
- MCP
Amazon Bedrock Knowledge Bases or RAGFlow: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.