--- title: "dagster vs starwhale" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dagster-io-dagster-vs-star-whale-starwhale" tools: ["dagster-io-dagster", "star-whale-starwhale"] --- # dagster vs starwhale *GraphCanon updated Sep 20, 2026* ## Verdict Pick dagster if dagster is an open-source orchestration platform developed in Python for managing and observing data pipelines and workflows; pick starwhale if starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. [dagster](https://dagster.io) reports 16k GitHub stars, 2.3k forks, and 2.6k open issues, last pushed Sep 11, 2026. [starwhale](https://starwhale.ai) has 235 stars, 37 forks, and 120 open issues, last pushed Dec 20, 2024. Figures are from public GitHub metadata via [dagster's repository](https://github.com/dagster-io/dagster) and [starwhale's repository](https://github.com/star-whale/starwhale). | | [dagster](/tools/dagster-io-dagster.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Tagline | An orchestration platform for data assets | an MLOps/LLMOps platform | | Stars | 16,144 | 235 | | Forks | 2,290 | 37 | | Open issues | 2,587 | 120 | | Language | Python | Java | | Adopt for | Dagster is an open-source orchestration platform developed in Python for managing and observing data pipelines and workflows. | Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. | | Categories | Data & Retrieval, Evaluation & Observability | Data & Retrieval, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dagster](/tools/dagster-io-dagster.md) | [starwhale](/tools/star-whale-starwhale.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 2d | 622d | | Open issues (now) | 2.6k | 120 | | Stars delta | +195 (30d) | -2 (30d) | | Open issues delta | -9 (30d) | 0 (30d) | | Full report | [trust report](/tools/dagster-io-dagster/trust.md) | [trust report](/tools/star-whale-starwhale/trust.md) | ## Decision facts: dagster - **Adopt for:** Dagster is an open-source orchestration platform developed in Python for managing and observing data pipelines and workflows. ## Decision facts: starwhale - **Requirements:** Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments. - **Adopt for:** Starwhale is an MLOps/LLMOps platform that focuses on model management for AI and large language models through various runtime setups. - **License detail:** Starwhale uses the Apache License 2.0, which is permissive and allows for usage in both open source and commercial applications with attribution. ## Choose when ### Choose dagster if… - dagster is primarily Python; starwhale is Java. - Tags unique to dagster: data-engineering, data-orchestrator, etl, mlops. - When your project requires an Apache-2.0 licensed tool allowing broader reuse and modification of code. ### Choose starwhale if… - starwhale is primarily Java; dagster is Python. - Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.. - Tags unique to starwhale: ai, cloud-native, dataset, datastore. - Also covers Inference & Serving, LLM Frameworks, Model Training. - When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ## When NOT to use dagster - If you are restricted to proprietary or non-open-source licenses, as Dagster's Apache-2.0 might not align with compliance requirements. - In environments where Python is not a preferred language, considering Dagster requires good knowledge of the Python ecosystem. - For teams that do not require or benefit from extensive documentation and hands-on tutorials for onboarding. - If specific features or integrations crucial to your workflow are found lacking in comparison to competitors. ## When NOT to use starwhale - In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. - For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ## Common questions ### What is the difference between dagster and starwhale? dagster: An orchestration platform for data assets. starwhale: an MLOps/LLMOps platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose dagster over starwhale? Choose dagster over starwhale when dagster is primarily Python; starwhale is Java; Tags unique to dagster: data-engineering, data-orchestrator, etl, mlops; When your project requires an Apache-2.0 licensed tool allowing broader reuse and modification of code. ### When should I choose starwhale over dagster? Choose starwhale over dagster when starwhale is primarily Java; dagster is Python; Requirements: Requires Docker; Supports runtime builds through Docker images for compatibility across various system environments.; Tags unique to starwhale: ai, cloud-native, dataset, datastore; Also covers Inference & Serving, LLM Frameworks, Model Training; When the need arises to manage models across different runtimes, including local environment configurations via runtime.yaml or conda environments, Docker images, or shell commands. ### When should I avoid dagster? If you are restricted to proprietary or non-open-source licenses, as Dagster's Apache-2.0 might not align with compliance requirements. In environments where Python is not a preferred language, considering Dagster requires good knowledge of the Python ecosystem. For teams that do not require or benefit from extensive documentation and hands-on tutorials for onboarding. If specific features or integrations crucial to your workflow are found lacking in comparison to competitors. ### When should I avoid starwhale? In scenarios where an exclusive user preference leans towards Python-based operations over Java and the tool's CLI interactions do not meet operational demands. For teams that require real-time model serving and have strict latency requirements, as Starwhale may not optimize for such use cases beyond its MLOps capabilities. ### Is dagster or starwhale more popular on GitHub? dagster has more GitHub stars (16,144 vs 235). Stars measure visibility, not whether either tool fits your constraints. ### Are dagster and starwhale open source? Yes - both are open-source projects on GitHub (dagster: Apache-2.0, starwhale: Apache-2.0). ### Where can I find alternatives to dagster or starwhale? GraphCanon lists graph-backed alternatives at [dagster alternatives](/tools/dagster-io-dagster/alternatives) and [starwhale alternatives](/tools/star-whale-starwhale/alternatives) ([dagster markdown twin](/tools/dagster-io-dagster/alternatives.md), [starwhale markdown twin](/tools/star-whale-starwhale/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/dagster-io-dagster-vs-star-whale-starwhale.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dagster or starwhale? dagster: Very active. starwhale: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for dagster and starwhale? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dagster trust report](/tools/dagster-io-dagster/trust); [starwhale trust report](/tools/star-whale-starwhale/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dagster-io-dagster`](/api/graphcanon/graph?tool=dagster-io-dagster) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_