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Apache Airflow vs Apache DolphinScheduler

A side-by-side comparison of two self-hosted automation & workflows options — licensing, setup difficulty, resource needs, and what each one replaces.

Not the right match-up?
AP Apache Airflow Programmatically author, schedule and monitor workflows VS AP Apache DolphinScheduler Distributed visual workflow scheduling platform
FeatureApache AirflowApache DolphinScheduler
Deploy effortUnder-an-hour setupUnder-an-hour setup
Health score100 · Excellent94 · Excellent
CategoryAutomation & WorkflowsAutomation & Workflows
LicenseApache-2.0Apache-2.0
LanguagePythonJava
Setup difficultyHardHard
Min. RAM4,096 MB2,048 MB
Deploymentdocker, kubernetes, helmdocker, kubernetes, bare-metal
GitHub stars★ 46,955★ 14,497
First released20152019
ReplacesAWS Step Functions, Azure Data FactoryAWS Step Functions, Azure Data Factory

What are Apache Airflow and Apache DolphinScheduler?

Apache Airflow

Apache Airflow is a platform to author, schedule and monitor workflows as directed acyclic graphs of tasks. It is widely used for data engineering pipelines and complex job orchestration.

  • Workflows defined as Python code
  • Rich scheduling and dependency management
  • Extensive operator and provider ecosystem
  • Web UI for monitoring DAGs

Read the full Apache Airflow guide →

Apache DolphinScheduler

Apache DolphinScheduler is a distributed, extensible workflow scheduler with a visual drag-and-drop interface. It is designed for big data and ETL job orchestration with high reliability.

  • Visual DAG workflow designer
  • Distributed and decentralized scheduling
  • Multi-tenant support
  • Rich task type plugins

Read the full Apache DolphinScheduler guide →

Apache Airflow vs Apache DolphinScheduler: key differences

Apache Airflow is written in Python, while Apache DolphinScheduler is built with Java. Apache DolphinScheduler is the lighter option, starting around 2,048 MB of RAM against 4,096 MB for Apache Airflow. Apache Airflow is the more established project (first released 2015), while Apache DolphinScheduler arrived in 2019. Apache Airflow has the considerably larger community, at 46,955 GitHub stars versus 14,497.

Why pick each one

Choose Apache Airflow if…

  • Industry standard for data pipelines
  • Huge ecosystem

Watch out for

  • Heavy to operate
  • Steep learning curve
Apache Airflow details

Choose Apache DolphinScheduler if…

  • Friendly visual interface
  • Scales horizontally

Watch out for

  • Heavy Java-based stack
Apache DolphinScheduler details

Frequently asked questions

Is Apache Airflow or Apache DolphinScheduler better?

Neither is universally better. Apache Airflow has the larger community; both share a hard setup difficulty, so the decision comes down to features and licensing.

Are Apache Airflow and Apache DolphinScheduler free and open-source?

Yes. Apache Airflow is licensed under Apache-2.0 and Apache DolphinScheduler under Apache-2.0. Both can be self-hosted at no software cost.

Can I run Apache Airflow and Apache DolphinScheduler with Docker?

Apache Airflow: yes. Apache DolphinScheduler: yes.

Which is lighter on resources, Apache Airflow or Apache DolphinScheduler?

Apache DolphinScheduler has the smaller minimum footprint at 2,048 MB of RAM, compared to about 4,096 MB for Apache Airflow. Real-world usage depends on library size, user count, and enabled features.

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