head to head · open source
graphrag vs ruoyi-ai
graphrag has 36,547 GitHub stars, 3,871 forks, 47 open issues and last shipped 3 days ago. ruoyi-ai has 5,805 stars, 1,430 forks, 7 open issues and last shipped 15 days ago. graphrag leads on adoption by 530% (36,547 vs 5,805 stars). graphrag is written in Python under MIT; ruoyi-ai is written in Java under MIT. graphrag has attracted 11% as many forks as stars, ruoyi-ai 25%. graphrag was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (rag), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
← all 20902 open source comparisons
Side by side
| graphrag | ruoyi-ai | |
|---|---|---|
| GitHub stars | ★ 37K | ★ 5.8K |
| License | MIT | MIT |
| Written in | Python | Java |
| Last push | 2026-11-02 | 2026-10-21 |
| Forks | ⑂ 3.9K | ⑂ 1.4K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick graphrag if
- You weight community size — 37K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick ruoyi-ai if
- You want the ruoyi-ai feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Java
- You evaluated both and ruoyi-ai fits your workflow better
About graphrag
GraphRAG [!WARNING] GraphRAG is a research project that explores the functional use of graphs to form a targeted context for question answering. Since our first release in July 2024 the capabilities of frontier models have changed dramatically, and our portfolio of research projects has diversified to match. This project is largely in maintenance mode, and won't be accepting new PRs or implementing new features. We'll perform bug fixes and dependency updates as appropriate, particularly to address CVEs as they arise. 👉 Microsoft Research Blog Post 👉 Read the docs 👉 GraphRAG Arxiv Overview The GraphRAG project…
read the full graphrag overview →
About ruoyi-ai
RuoYi AI [![Contributors][contributors shield]][contributors url] [![Forks][forks shield]][forks url] [![Stargazers][stars shield]][stars url] [![Issues][issues shield]][issues url] [![MIT License][license shield]][license url] Enterprise Grade AI Assistant Platform An out of the box full stack AI platform supporting multi agent collaboration, Supervisor mode orchestration, and multiple decision models, with advanced RAG technology and visual workflow orchestration capabilities 中文 📖 Documentation 🚀 Live Demo 🐛 Report Issues 💡 Feature Requests 🚀 Live Demo ✨ Core Features Project Repositories Partner Projects…
read the full ruoyi-ai overview →
More in AI & Machine Learning
Related comparisons
More AI Development Platforms projects
Compare either of these against the rest of the AI Development Platforms field.
Frequently asked questions
Is graphrag or ruoyi-ai more popular?
graphrag has 36,547 GitHub stars and ruoyi-ai has 5,805. graphrag has the larger community by that measure.
Are graphrag and ruoyi-ai free?
Both are open source. graphrag is licensed under MIT and ruoyi-ai under MIT. Neither carries a licence fee.
What is the difference between graphrag and ruoyi-ai?
graphrag is written in Python and ruoyi-ai in Java. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, graphrag or ruoyi-ai?
Choose graphrag if you want the larger community (36,547 stars) or its MIT licence terms. Choose ruoyi-ai if its feature set, stack or MIT licence fits better. Both are self-hostable.