Dify vs RamaLama
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?
Dify
Open-source platform for building production LLM apps
VS
RamaLama
Run AI models using OCI containers
| Feature | Dify | RamaLama |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | Apache-2.0 | MIT |
| Language | TypeScript | Python |
| Setup difficulty | Medium | Medium |
| Min. RAM | 4,096 MB | 8,192 MB |
| Deployment | docker, kubernetes, helm | docker, kubernetes, bare-metal |
| GitHub stars | ★ 151,746 | ★ 2,990 |
| First released | 2023 | 2024 |
| Replaces | OpenAI Assistants, Vertex AI Agent Builder | Ollama |
Why pick each one
Choose Dify if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 151.7k GitHub stars
Choose RamaLama if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Active community (3k GitHub stars)
Frequently asked questions
Is Dify or RamaLama better?
Neither is universally better. Dify has the larger community; both share a medium setup difficulty, so the decision comes down to features and licensing.
Are Dify and RamaLama free and open-source?
Yes. Dify is licensed under Apache-2.0 and RamaLama under MIT. Both can be self-hosted at no software cost.
Can I run Dify and RamaLama with Docker?
Dify: yes. RamaLama: yes.