apache/dolphinscheduler

Health v2 · maintenance only

Adoption not part of the score

14447 stars · 5084 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Apache DolphinScheduler is a modern data orchestration platform for building high-performance workflows with low-code drag-and-drop tooling, a Python SDK, or Open API. It features a decentralized multi-master/multi-worker architecture with high availability, horizontal scaling, and support for deployment on standalone, Docker, and Kubernetes environments.

Use cases

• orchestrate complex data pipelines with task dependencies
• schedule and monitor batch ETL jobs
• replace Airflow or Azkaban with a low-code workflow scheduler
• run workflows across multiple clouds and data centers
• manage multi-tenant job scheduling with permission control
• backfill and version-control workflow runs
• deploy a high-availability task scheduler on Kubernetes

When to choose

• you need a visual, low-code DAG builder for data pipelines
• you require tens of millions of tasks per day with horizontal scaling
• you want decentralized multi-master/multi-worker high availability out of the box
• you need multi-cloud, multi-tenancy, and fine-grained permission control
• you prefer a Web UI, Python SDK, or Open API for workflow management

When to avoid

• your team is already invested in Airflow's Python-native DAG ecosystem
• you only need simple cron-style scheduling without complex dependencies
• you want a lightweight single-node scheduler with minimal infrastructure
• your workflows are tightly coupled to a platform-specific orchestrator like AWS Step Functions

Facets

application · maturity stable

workflow-automation scheduling etl deployment web-framework big-data cloud-computing self-hosted jvm self-hosted cloud workflow-orchestration data-pipelines task-scheduler low-code airflow-alternative azkaban-alternative multi-tenancy distributed-systems data-engineering automation docker kubernetes web-server

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