Home/Compare/airflow vs dolphinscheduler

Comparison

airflow vs dolphinscheduler

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.

Markdown twin · airflow alternatives · dolphinscheduler alternatives

GraphCanon updated Sep 14, 2026

13views this month

airflow logo

airflow

apache/airflow

47kpushed Sep 14, 2026
vs
dolphinscheduler logo

dolphinscheduler

apache/dolphinscheduler

14kpushed Sep 12, 2026

Trust & integrity

Signalairflowdolphinscheduler
Maintenance
Very active (0d since push)
As of Sep 14, 2026 · github_public_v1
Very active (2d since push)
As of Sep 14, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 14, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 14, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 15, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 15, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

airflow
A platform to programmatically author, schedule, and monitor workflows
dolphinscheduler
A modern data orchestration platform for agile workflow creation with low-code

Stars

airflow
47k
dolphinscheduler
14k

Forks

airflow
18k
dolphinscheduler
5.1k

Open issues

airflow
2.1k
dolphinscheduler
132

Language

airflow
Python
dolphinscheduler
Java

Adopt for

airflow
Apache Airflow is a Python-based orchestrator for scheduling and monitoring workflows, suitable for tasks that require flexible DAG (Directed Acyclic Graph) definitions.
dolphinscheduler
Apache DolphinScheduler is a modern data orchestration platform designed for efficient task dependency handling in data pipelines and provides low-code workflow creation.

Persona

airflow
-
dolphinscheduler
-

Runtime

airflow
-
dolphinscheduler
-

License

airflow
Apache-2.0
dolphinscheduler
Apache-2.0

Last pushed

airflow
Sep 14, 2026
dolphinscheduler
Sep 12, 2026

Categories

airflow
Developer Tools
dolphinscheduler
Developer Tools

Trust and health

Days since push

airflow
0d
dolphinscheduler
2d

Open issues (now)

airflow
2.1k
dolphinscheduler
132

Stars delta

airflow
+419 (30d)
dolphinscheduler
+57 (30d)

Open issues delta

airflow
+262 (30d)
dolphinscheduler
-5 (30d)

Full report

dolphinscheduler
Trust report

Shared compatibility

  • Python · airflow: Python runtime · dolphinscheduler: Python runtime

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).

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.

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 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: airflow 47k · dolphinscheduler 14k (synced Sep 14, 2026).

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 and dolphinscheduler alternatives (airflow markdown twin, dolphinscheduler markdown twin), 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 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; dolphinscheduler trust report.

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