head to head · open source
Dify vs R2R
Dify has 160,251 GitHub stars, 25,336 forks, 1,067 open issues and last shipped yesterday. R2R has 8,055 stars, 650 forks, 126 open issues and last shipped 12 months ago. Dify leads on adoption by 1,889% (160,251 vs 8,055 stars). Dify is written in Python under a custom or non-standard licence; R2R is written in Python under MIT. Dify has attracted 16% as many forks as stars, R2R 8%. Dify was the more recently maintained of the two, and both are self-hostable with no licence fee.
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
| Dify | R2R | |
|---|---|---|
| GitHub stars | ★ 160K | ★ 8.1K |
| License | Custom / other | MIT |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2025-11-07 |
| Forks | ⑂ 25K | ⑂ 650 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Dify if
- You weight community size — 160K stars and counting
- You want the Custom / other license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick R2R if
- You want the R2R feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and R2R fits your workflow better
About Dify
Dify Cloud · Self hosting · Documentation · Dify edition overview Dify is an open source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. Here's a list of the core features: Quick start Before installing Dify, make sure your machine meets the following minimum system requirements: CPU = 2 Core RAM = 4 GiB The easiest way to start the Dify server is through Docker Compose. Before running Dify with the…
About R2R
The most advanced AI retrieval system. Agentic Retrieval Augmented Generation (RAG) with a RESTful API. Docs · Report Bug · Feature Request · Discord About R2R is an advanced AI retrieval system supporting Retrieval Augmented Generation (RAG) with production ready features. Built around a RESTful API, R2R offers multimodal content ingestion, hybrid search, knowledge graphs, and comprehensive document management. R2R also includes a Deep Research API , a multi step reasoning system that fetches relevant data from your knowledgebase and/or the internet to deliver richer, context aware answers for complex queries…
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 Dify or R2R more popular?
Dify has 160,251 GitHub stars and R2R has 8,055. Dify has the larger community by that measure.
Are Dify and R2R free?
Both are open source. Dify has no licence declared in this registry, and R2R is licensed under MIT. Both are free to self-host.
What is the difference between Dify and R2R?
Dify is written in Python and R2R in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Dify or R2R?
Choose Dify if you want the larger community (160,251 stars) or its Custom / other licence terms. Choose R2R if its feature set, stack or MIT licence fits better. Both are self-hostable.