head to head · open source
vllm vs dagster
vllm has 96,158 GitHub stars, 24,317 forks, 7,953 open issues and last shipped yesterday. dagster has 16,364 stars, 2,395 forks, 2,589 open issues and last shipped 4 days ago. vllm leads on adoption by 488% (96,158 vs 16,364 stars). vllm is written in Python under Apache-2.0; dagster is written in Python under Apache-2.0. vllm has attracted 25% as many forks as stars, dagster 15%. vllm 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.
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Side by side
| vllm | dagster | |
|---|---|---|
| GitHub stars | ★ 96K | ★ 16K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-10-30 |
| Forks | ⑂ 24K | ⑂ 2.4K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick vllm if
- You weight community size — 96K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick dagster if
- You want the dagster feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and dagster fits your workflow better
About vllm
Easy, fast, and cheap LLM serving for everyone 🔥 We have built a vLLM website to help you get started with vLLM. Please visit vllm.ai to learn more. For events, please visit vllm.ai/events to join us. About vLLM is a fast and easy to use library for LLM inference and serving. Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has grown into one of the most active open source AI projects built and maintained by a diverse community of many dozens of academic institutions and companies from over 2000 contributors. vLLM is fast with: State of the art serving throughput Efficient management of…
About dagster
Dagster is a cloud native data pipeline orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best in class testability. It is designed for developing and maintaining data assets , such as tables, data sets, machine learning models, and reports. With Dagster, you declare—as Python functions—the data assets that you want to build. Dagster then helps you run your functions at the right time and keep your assets up to date. Here is an example of a graph of three assets defined in Python: The graph loaded into Dagster's web UI: Dagster is…
read the full dagster overview →
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Frequently asked questions
Is vllm or dagster more popular?
vllm has 96,158 GitHub stars and dagster has 16,364. vllm has the larger community by that measure.
Are vllm and dagster free?
Both are open source. vllm is licensed under Apache-2.0 and dagster under Apache-2.0. Neither carries a licence fee.
What is the difference between vllm and dagster?
vllm is written in Python and dagster 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, vllm or dagster?
Choose vllm if you want the larger community (96,158 stars) or its Apache-2.0 licence terms. Choose dagster if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.