RAGFlow vs Rasa Open Source
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
RAGFlow
RAG engine with deep document understanding
VS
Rasa Open Source
Framework for building contextual text and voice assistants
| Feature | RAGFlow | Rasa Open Source |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | Apache-2.0 | Apache-2.0 |
| Language | Go | Python |
| Setup difficulty | Medium | Hard |
| Min. RAM | 8,192 MB | 2,048 MB |
| Deployment | docker, kubernetes | docker, source |
| GitHub stars | ★ 87,057 | ★ 21,288 |
| First released | 2024 | 2017 |
| Replaces | NotebookLM | Dialogflow, Amazon Lex |
Why pick each one
Choose RAGFlow if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 87.1k GitHub stars
Choose Rasa Open Source if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Mature project with 21.3k GitHub stars
- Written in Python
Frequently asked questions
Is RAGFlow or Rasa Open Source better?
RAGFlow is the stronger all-round pick: it has both the larger community and the simpler medium setup. Consider Rasa Open Source if its specific feature set fits your needs better.
Are RAGFlow and Rasa Open Source free and open-source?
Yes. RAGFlow is licensed under Apache-2.0 and Rasa Open Source under Apache-2.0. Both can be self-hosted at no software cost.
Can I run RAGFlow and Rasa Open Source with Docker?
RAGFlow: yes. Rasa Open Source: yes.