Overview

RAGFlow vs MaxKB: choosing an open-source RAG engine

RAGFlow (88k+ stars, Apache-2.0) is an enterprise-grade open-source RAG engine with deep document understanding and Agent capabilities, deployable via Docker. MaxKB (22k+ stars, GPL-3.0) is an open-source knowledge base Q&A and Agent-building platform focused on zero-code integration and workflow orchestration. We compare retrieval capabilities, document processing, deployment, and typical scenarios.

Projects Compared

RAGFlow

Go · Apache-2.0

88.6k ★

A leading open-source RAG engine that fuses cutting-edge retrieval-augmented generation with agent capabilities to create a superior context layer for LLMs.

ragdocument-understandingknowledge-baseretrievalocr
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Feature Comparison

Best for RAGFlow
Product positioning Open-source RAG engine focused on deep document understanding, knowledge extraction, and Agent capabilities. Enterprise-grade, "a superior context layer for LLMs."
Retrieval capabilities Multi-path recall with fused re-ranking. Supports multiple embedding models and LLM configurations. Template-based chunking with strong explainability.
Document processing DeepDoc: supports Word, PPT, Excel, TXT, images, scanned documents, structured data, and web pages. Template-based chunking with traceable citations.
Deployment Docker Compose one-click deployment. GPU acceleration for DeepDoc tasks. Managed cloud service at cloud.ragflow.io. Main service Python (ragflow_server.py); Go is used for sandbox executor.
Best fit Enterprise RAG applications, complex document understanding, compliance scenarios needing traceable citations, teams with existing Docker infrastructure.

GitHub Stats

Metric RAGFlow
Stars 88.6k
Forks 10.4k
Language Go
License Apache-2.0
Last commit August 16, 2026

Which one should you choose?

Choose based on your primary workflow, language ecosystem, and integration needs. Review each project's documentation and recent GitHub activity before adopting it in production.

Frequently asked questions

Which has better Chinese language support?

Both are Chinese-friendly. RAGFlow has DeepDoc for extracting text from Chinese scanned documents and PDFs. MaxKB supports multi-modal input for Chinese knowledge base Q&A.

Which is easier to deploy?

MaxKB is simpler: a single Docker command. RAGFlow needs Docker Compose but has good documentation. For non-technical users, MaxKB is faster to get started.

Can RAGFlow and MaxKB integrate with LangChain?

Both support multiple LLM and embedding models. RAGFlow's backend can connect to the LangChain ecosystem. MaxKB has built-in LangChain framework for more direct integration.

Which is better for production?

RAGFlow scales to enterprise-grade RAG (88k stars, Apache-2.0, GPU acceleration). MaxKB suits small-to-medium teams building knowledge bases quickly (22k stars, GPL-3.0).