--- title: "airflow vs dolphinscheduler" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/apache-airflow-vs-apache-dolphinscheduler" tools: ["apache-airflow", "apache-dolphinscheduler"] --- # airflow vs dolphinscheduler *GraphCanon updated Sep 20, 2026* ## Verdict Pick airflow if apache Airflow is a Python-based orchestrator for scheduling and monitoring workflows, suitable for tasks that require flexible DAG (Directed Acyclic Graph) definitions; 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. [airflow](https://airflow.apache.org/) reports 47k GitHub stars, 18k forks, and 2.1k open issues, last pushed Sep 14, 2026. [dolphinscheduler](https://dolphinscheduler.apache.org/) has 14k stars, 5.1k forks, and 132 open issues, last pushed Sep 12, 2026. Figures are from public GitHub metadata via [airflow's repository](https://github.com/apache/airflow) and [dolphinscheduler's repository](https://github.com/apache/dolphinscheduler). | | [airflow](/tools/apache-airflow.md) | [dolphinscheduler](/tools/apache-dolphinscheduler.md) | | --- | --- | --- | | Tagline | A platform to programmatically author, schedule, and monitor workflows | A modern data orchestration platform for agile workflow creation with low-code | | Stars | 46,844 | 14,469 | | Forks | 17,829 | 5,091 | | Open issues | 2,144 | 132 | | Language | Python | Java | | Adopt for | Apache Airflow is a Python-based orchestrator for scheduling and monitoring workflows, suitable for tasks that require flexible DAG (Directed Acyclic Graph) definitions. | Apache DolphinScheduler is a modern data orchestration platform designed for efficient task dependency handling in data pipelines and provides low-code workflow creation. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Developer Tools | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [airflow](/tools/apache-airflow.md) | [dolphinscheduler](/tools/apache-dolphinscheduler.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 2.1k | 132 | | Stars delta | +419 (30d) | +57 (30d) | | Open issues delta | +262 (30d) | -5 (30d) | | Full report | [trust report](/tools/apache-airflow/trust.md) | [trust report](/tools/apache-dolphinscheduler/trust.md) | ## Shared compatibility - **Python**: [airflow](/tools/apache-airflow.md) - Python runtime; [dolphinscheduler](/tools/apache-dolphinscheduler.md) - Python runtime ## Decision facts: airflow - **Adopt for:** Apache Airflow is a Python-based orchestrator for scheduling and monitoring workflows, suitable for tasks that require flexible DAG (Directed Acyclic Graph) definitions. ## 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. ## Choose when ### Choose airflow if… - airflow is primarily Python; dolphinscheduler is Java. - Tags unique to airflow: apache, automation, dag, data-engineering. - airflow ships Docker support for self-hosted deployment. - If you need to model complex workflow dependency graphs with Directed Acyclic Graphs (DAGs). ### Choose dolphinscheduler if… - dolphinscheduler is primarily Java; airflow is Python. - Tags unique to dolphinscheduler: azkaban, cloud-native, 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 NOT to use airflow - Avoid if you require Windows as the primary execution environment without using WSL2. - If your project strictly adheres to MariaDB for database management, Airflow is not recommended because it is neither tested nor supported by the tool. ## 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. ## Common questions ### What is the difference between airflow and dolphinscheduler? airflow: A platform to programmatically author, schedule, and monitor workflows. dolphinscheduler: A modern data orchestration platform for agile workflow creation with low-code. See the comparison table for live GitHub stats and shared categories. ### When should I choose airflow over dolphinscheduler? Choose airflow over dolphinscheduler when airflow is primarily Python; dolphinscheduler is Java; Tags unique to airflow: apache, automation, dag, data-engineering; airflow ships Docker support for self-hosted deployment; If you need to model complex workflow dependency graphs with Directed Acyclic Graphs (DAGs). ### When should I choose dolphinscheduler over airflow? Choose dolphinscheduler over airflow when dolphinscheduler is primarily Java; airflow is Python; Tags unique to dolphinscheduler: azkaban, cloud-native, 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 avoid airflow? Avoid if you require Windows as the primary execution environment without using WSL2. If your project strictly adheres to MariaDB for database management, Airflow is not recommended because it is neither tested nor supported by the tool. ### 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. ### Is airflow or dolphinscheduler more popular on GitHub? airflow has more GitHub stars (46,844 vs 14,469). Stars measure visibility, not whether either tool fits your constraints. ### Are airflow and dolphinscheduler open source? Yes - both are open-source projects on GitHub (airflow: Apache-2.0, dolphinscheduler: Apache-2.0). ### Where can I find alternatives to airflow or dolphinscheduler? GraphCanon lists graph-backed alternatives at [airflow alternatives](/tools/apache-airflow/alternatives) and [dolphinscheduler alternatives](/tools/apache-dolphinscheduler/alternatives) ([airflow markdown twin](/tools/apache-airflow/alternatives.md), [dolphinscheduler markdown twin](/tools/apache-dolphinscheduler/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-airflow-vs-apache-dolphinscheduler.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, airflow or dolphinscheduler? airflow: Very active. dolphinscheduler: 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 airflow and dolphinscheduler? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [airflow trust report](/tools/apache-airflow/trust); [dolphinscheduler trust report](/tools/apache-dolphinscheduler/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=apache-airflow`](/api/graphcanon/graph?tool=apache-airflow) - 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/_