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apache/dolphinscheduler

A distributed, low-code data orchestration platform for building, scheduling and monitoring complex data pipeline workflows.

Open-source alternative to:Apache Airflow CloudControl-MAzkaban

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What is it?

Apache DolphinScheduler is a workflow orchestration platform for data pipelines. Users define tasks and their dependencies, then schedule and monitor them from a Web UI, a Python SDK or an Open API. It ships with a wide range of built-in task types, so common jobs can be assembled by drag and drop without writing scheduling code.

The platform uses a decentralized, multi-master and multi-worker architecture intended for horizontal scaling. It can be deployed in Standalone, Cluster, Docker or Kubernetes modes. Workflows and individual workflow instances are version controlled, and running workflows and tasks can be paused, stopped or recovered at any time. Multi-tenancy and permission control for projects and data sources are included, along with backfill support.

The project also provides a monitor view that shows the status of masters, workers and the database, including server resource usage, and it can connect to external data sources such as MySQL, PostgreSQL, Hive and Trino.

Key features

  • 01Drag-and-drop workflow design in a Web UI, plus Python SDK and Open API access.
  • 02Multiple deployment modes: Standalone, Cluster, Docker and Kubernetes.
  • 03Multi-master, multi-worker architecture that scales horizontally.
  • 04Workflow and task versioning with pause, stop and recovery controls.
  • 05Multi-tenancy with project and data source permission control.
  • 06Built-in backfill and a monitor view for master, worker and database health.

Use cases

  • Scheduling recurring ETL or data warehouse jobs with dependencies between tasks.
  • Orchestrating data workflows across multiple clouds or data centers.
  • Giving several teams isolated projects and permissions on a shared scheduling platform.
  • Running containerized tasks on a Kubernetes cluster.

Quick start

  1. 1

    Start quickly with Docker

  2. 2

    Start in standalone mode

  3. 3

    Deploy on Kubernetes

Things to know

  • Deployment is multi-component, so self-hosting takes real setup effort beyond a single install command.
  • The README's quick start links point to the 3.3.0-alpha documentation rather than a single one-line install.

Topics

#workflow-orchestration#data-pipelines#job-scheduler#low-code#distributed-systems#kubernetes#etl#airflow#azkaban#cloud-native

FAQ

What is dolphinscheduler?
A distributed, low-code data orchestration platform for building, scheduling and monitoring complex data pipeline workflows. Apache DolphinScheduler is a workflow orchestration platform for data pipelines. Users define tasks and their dependencies, then schedule and monitor them from a Web UI, a Python SDK or an Open API. It ships with a wide range of built-in task types, so common jobs can be assembled by drag and drop without writing scheduling code.
Is dolphinscheduler free to use? What license does it have?
dolphinscheduler is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is dolphinscheduler still maintained?
Actively maintained. The last commit to dolphinscheduler was on Oct 21, 2026.
What can I use dolphinscheduler for?
Scheduling recurring ETL or data warehouse jobs with dependencies between tasks. Orchestrating data workflows across multiple clouds or data centers. Giving several teams isolated projects and permissions on a shared scheduling platform. Running containerized tasks on a Kubernetes cluster.
How do I install dolphinscheduler?
Start quickly with Docker Start in standalone mode Deploy on Kubernetes
Where can I get dolphinscheduler?
The source code and installation instructions are on GitHub: https://github.com/apache/dolphinscheduler

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