BentoML vs RAGFlow
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?
BentoML
Framework for building and serving AI model APIs
VS
RAGFlow
RAG engine with deep document understanding
| Feature | BentoML | RAGFlow |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | Apache-2.0 | Apache-2.0 |
| Language | Python | Go |
| Setup difficulty | Medium | Medium |
| Min. RAM | 2,048 MB | 8,192 MB |
| Deployment | docker, kubernetes, source | docker, kubernetes |
| GitHub stars | ★ 8,768 | ★ 87,057 |
| First released | 2019 | 2024 |
| Replaces | Amazon SageMaker, Vertex AI | NotebookLM |
Why pick each one
Choose BentoML if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 8.8k GitHub stars
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
Frequently asked questions
Is BentoML or RAGFlow better?
Neither is universally better. RAGFlow has the larger community; both share a medium setup difficulty, so the decision comes down to features and licensing.
Are BentoML and RAGFlow free and open-source?
Yes. BentoML is licensed under Apache-2.0 and RAGFlow under Apache-2.0. Both can be self-hosted at no software cost.
Can I run BentoML and RAGFlow with Docker?
BentoML: yes. RAGFlow: yes.