head to head · open source

dagster vs Olares

dagster has 16,183 GitHub stars, 2,296 forks, 2,589 open issues and last shipped 2 days ago. Olares has 5,278 stars, 329 forks, 155 open issues and last shipped yesterday. dagster leads on adoption by 207% (16,183 vs 5,278 stars). dagster is written in Python under Apache-2.0; Olares is written in Go under AGPL-3.0. dagster has attracted 14% as many forks as stars, Olares 6%. Olares 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.

dagster ★ 16K Olares ★ 5.3K category AI & Machine Learning

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Side by side

dagster Olares
GitHub stars ★ 16K ★ 5.3K
License Apache-2.0 AGPL-3.0
Written in Python Go
Last push 2026-09-18 2026-09-19
Forks ⑂ 2.3K ⑂ 329
Self-hosting Yes Yes
Data ownership Your server Your server

pick dagster if

  • You weight community size — 16K 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

full dagster profile →

pick Olares if

  • You want the Olares feature set and don't need the biggest community
  • You prefer the AGPL-3.0 license terms
  • Your stack matches Go
  • You evaluated both and Olares fits your workflow better

full Olares profile →

About dagster

Dagster is a cloud native data pipeline orchestrator written in Python and released under the Apache 2.0 licence, built for data engineers, data scientists, and machine learning teams who declare the tables, data sets, models, and reports their pipelines should produce and need those assets tested, observable, and kept up to date from local development through production.

read the full dagster overview →

About Olares

Olares is an open source personal cloud operating system built to run AI agents and large language models on hardware you own. It is written in Go and released under the AGPL 3.0 license, and it sits in the cloud native and self hosted corner of the machine learning infrastructure ecosystem. The project describes itself as an operating system you operate in plain language, powered by Kubernetes, turning a machine or a set of machines into a self hosted AI platform reachable from any browser.

read the full Olares overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

Related comparisons

openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

dagster vs Ollama dagster vs llama.cpp dagster vs vllm dagster vs GPT4All dagster vs llama_index dagster vs LocalAI dagster vs faiss dagster vs PageIndex dagster vs Langfuse dagster vs cognee dagster vs taipy dagster vs zvec

Frequently asked questions

Is dagster or Olares more popular?

dagster has 16,183 GitHub stars and Olares has 5,278. dagster has the larger community by that measure.

Are dagster and Olares free?

Both are open source. dagster is licensed under Apache-2.0 and Olares under AGPL-3.0. Neither carries a licence fee.

What is the difference between dagster and Olares?

dagster is written in Python and Olares in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, dagster or Olares?

Choose dagster if you want the larger community (16,183 stars) or its Apache-2.0 licence terms. Choose Olares if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.