--- title: "dolphinscheduler vs argo-workflows" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apache-dolphinscheduler-vs-argoproj-argo-workflows" tools: ["apache-dolphinscheduler", "argoproj-argo-workflows"] --- # dolphinscheduler vs argo-workflows *GraphCanon updated Sep 20, 2026* ## Verdict Pick dolphinscheduler if apache DolphinScheduler is a modern data orchestration platform designed for efficient task dependency handling in data pipelines and provides low-code workflow creation; pick argo-workflows if argo Workflows, an open-source workflow engine for Kubernetes implemented as a CRD, is popular due to its lightweight design, scalability, and extensive artifact support. [dolphinscheduler](https://dolphinscheduler.apache.org/) reports 14k GitHub stars, 5.1k forks, and 132 open issues, last pushed Sep 12, 2026. [argo-workflows](https://argo-workflows.readthedocs.io/) has 17k stars, 3.6k forks, and 1.3k open issues, last pushed Sep 3, 2026. Figures are from public GitHub metadata via [dolphinscheduler's repository](https://github.com/apache/dolphinscheduler) and [argo-workflows's repository](https://github.com/argoproj/argo-workflows). | | [dolphinscheduler](/tools/apache-dolphinscheduler.md) | [argo-workflows](/tools/argoproj-argo-workflows.md) | | --- | --- | --- | | Tagline | A modern data orchestration platform for agile workflow creation with low-code | Workflow Engine for Kubernetes | | Stars | 14,469 | 16,956 | | Forks | 5,091 | 3,643 | | Open issues | 132 | 1,269 | | Language | Java | Go | | Adopt for | Apache DolphinScheduler is a modern data orchestration platform designed for efficient task dependency handling in data pipelines and provides low-code workflow creation. | Argo Workflows, an open-source workflow engine for Kubernetes implemented as a CRD, is popular due to its lightweight design, scalability, and extensive artifact support. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Developer Tools | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dolphinscheduler](/tools/apache-dolphinscheduler.md) | [argo-workflows](/tools/argoproj-argo-workflows.md) | | --- | --- | --- | | Days since push | 2d | 0d | | Open issues (now) | 132 | 1.3k | | Stars delta | +57 (30d) | +89 (30d) | | Open issues delta | -5 (30d) | -52 (30d) | | Full report | [trust report](/tools/apache-dolphinscheduler/trust.md) | [trust report](/tools/argoproj-argo-workflows/trust.md) | ## Shared compatibility - **Python**: [dolphinscheduler](/tools/apache-dolphinscheduler.md) - Python runtime; [argo-workflows](/tools/argoproj-argo-workflows.md) - Python runtime ## Decision facts: dolphinscheduler - **Adopt for:** Apache DolphinScheduler is a modern data orchestration platform designed for efficient task dependency handling in data pipelines and provides low-code workflow creation. ## Decision facts: argo-workflows - **Adopt for:** Argo Workflows, an open-source workflow engine for Kubernetes implemented as a CRD, is popular due to its lightweight design, scalability, and extensive artifact support. ## Choose when ### Choose dolphinscheduler if… - dolphinscheduler is primarily Java; argo-workflows is Go. - Tags unique to dolphinscheduler: airflow, azkaban, data-pipelines, job-scheduler. - You require extensive support for complex task dependencies within your data pipelines, as Dolphinscheduler is built to handle these scenarios out of the box. ### Choose argo-workflows if… - argo-workflows is primarily Go; dolphinscheduler is Java. - Tags unique to argo-workflows: machine-learning, mlops, pipelines, workflow-engine. - Also covers Model Training. - argo-workflows ships Docker support for self-hosted deployment. - When orchestrating container-native workflows for tasks like machine learning or data processing on Kubernetes ## When NOT to use dolphinscheduler - If your organization has stringent licensing constraints that restrict the use of Apache-2.0 licensed software - Your workflows are relatively simple and do not require advanced features such as versioning for both workflows and instances, multi-tenancy support or backfill capability. - You prefer a tool that is primarily script-driven over one with extensive SDKs and APIs; Dolphinscheduler emphasizes its Web UI for ease of use along with Python SDKs and Open APIs. ## When NOT to use argo-workflows - In non-Kubernetes environments due to its tight integration with Kubernetes CRDs and native features - For legacy system migrations that require significant VM and server-based overheads, as Argo Workflows is container-centric without such layers ## Common questions ### What is the difference between dolphinscheduler and argo-workflows? dolphinscheduler: A modern data orchestration platform for agile workflow creation with low-code. argo-workflows: Workflow Engine for Kubernetes. See the comparison table for live GitHub stats and shared categories. ### When should I choose dolphinscheduler over argo-workflows? Choose dolphinscheduler over argo-workflows when dolphinscheduler is primarily Java; argo-workflows is Go; Tags unique to dolphinscheduler: airflow, azkaban, data-pipelines, job-scheduler; You require extensive support for complex task dependencies within your data pipelines, as Dolphinscheduler is built to handle these scenarios out of the box. ### When should I choose argo-workflows over dolphinscheduler? Choose argo-workflows over dolphinscheduler when argo-workflows is primarily Go; dolphinscheduler is Java; Tags unique to argo-workflows: machine-learning, mlops, pipelines, workflow-engine; Also covers Model Training; argo-workflows ships Docker support for self-hosted deployment; When orchestrating container-native workflows for tasks like machine learning or data processing on Kubernetes. ### When should I avoid dolphinscheduler? If your organization has stringent licensing constraints that restrict the use of Apache-2.0 licensed software Your workflows are relatively simple and do not require advanced features such as versioning for both workflows and instances, multi-tenancy support or backfill capability. You prefer a tool that is primarily script-driven over one with extensive SDKs and APIs; Dolphinscheduler emphasizes its Web UI for ease of use along with Python SDKs and Open APIs. ### When should I avoid argo-workflows? In non-Kubernetes environments due to its tight integration with Kubernetes CRDs and native features For legacy system migrations that require significant VM and server-based overheads, as Argo Workflows is container-centric without such layers ### Is dolphinscheduler or argo-workflows more popular on GitHub? argo-workflows has more GitHub stars (16,956 vs 14,469). Stars measure visibility, not whether either tool fits your constraints. ### Are dolphinscheduler and argo-workflows open source? Yes - both are open-source projects on GitHub (dolphinscheduler: Apache-2.0, argo-workflows: Apache-2.0). ### Where can I find alternatives to dolphinscheduler or argo-workflows? GraphCanon lists graph-backed alternatives at [dolphinscheduler alternatives](/tools/apache-dolphinscheduler/alternatives) and [argo-workflows alternatives](/tools/argoproj-argo-workflows/alternatives) ([dolphinscheduler markdown twin](/tools/apache-dolphinscheduler/alternatives.md), [argo-workflows markdown twin](/tools/argoproj-argo-workflows/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/apache-dolphinscheduler-vs-argoproj-argo-workflows.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dolphinscheduler or argo-workflows? dolphinscheduler: Very active. argo-workflows: Very active. 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 dolphinscheduler and argo-workflows? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dolphinscheduler trust report](/tools/apache-dolphinscheduler/trust); [argo-workflows trust report](/tools/argoproj-argo-workflows/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=apache-dolphinscheduler`](/api/graphcanon/graph?tool=apache-dolphinscheduler) - 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/_