OpenRAG VS RAGFlow

Let’s have a side-by-side comparison of OpenRAG vs RAGFlow to find out which one is better. This software comparison between OpenRAG and RAGFlow is based on genuine user reviews. Compare software prices, features, support, ease of use, and user reviews to make the best choice between these, and decide whether OpenRAG or RAGFlow fits your business.

OpenRAG

OpenRAG
OpenRag is a lightweight, modular and extensible Retrieval-Augmented Generation (RAG) framework designed to explore and test advanced RAG techniques — 100% open source and focused on experimentation, not lock-in.

RAGFlow

RAGFlow
RAGFlow: The RAG engine for production AI. Build accurate, reliable LLM apps with deep document understanding, grounded citations & reduced hallucinations.

OpenRAG

Launched 2025-07
Pricing Model Free
Starting Price
Tech used
Tag

RAGFlow

Launched 2024-02
Pricing Model Free
Starting Price
Tech used Vercel,Atom,Gzip,OpenGraph,RSS,HSTS
Tag Knowledge Management,Question Answering,Data Extraction

OpenRAG Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

RAGFlow Rank/Visit

Global Rank 144118
Country China
Month Visit 231017

Top 5 Countries

49.33%
14.38%
6.29%
5.09%
3.91%
China United States Vietnam Singapore Germany

Traffic Sources

0.8%
0.33%
0.03%
11.91%
31.01%
55.91%
social paidReferrals mail referrals search direct

Estimated traffic data from Similarweb

What are some alternatives?

When comparing OpenRAG and RAGFlow, you can also consider the following products

R2R - SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.

ApeRAG - ApeRAG: Production-ready GraphRAG for intelligent AI agents. Unlock deep context & reliable reasoning from all your multi-modal enterprise data.

UltraRAG - UltraRAG 2.0: Build complex RAG pipelines with low-code. Accelerate AI research, simplify development, and ensure reproducible results.

HelloRAG.ai - HelloRAG is a no-code, easy-to-use and scalable solution to ingest human and machine generated multi-modal data for LLM-powered applications

More Alternatives