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Apache DolphinScheduler
What it is
Apache DolphinScheduler is a free, open-source workflow orchestration platform for building data workflows with visual DAG interfaces or code. Users can design flows by dragging and dropping tasks or by using Python, YAML or the Open API. The project lists more than 30 built-in task types, including Shell, SQL, Spark, Flink, Hive, Kubernetes and HTTP. Workflows can link projects and other workflows, pause or resume, and run batch backfills serially or in parallel. Its decentralized multi-master and multi-worker architecture is described as increasing scheduling capacity with cluster size. Deployment options are standalone, cluster and Kubernetes. Standalone is intended for evaluation, recommended for fewer than 20 workflows, and its in-memory H2 database is cleared on service stop or restart. Authentication includes password, LDAP, Casdoor SSO and OAuth2. The security model assumes a secure network and does not address internal cross-infiltration.
For and against
For
- Free and open-source
- Visual DAG builder plus Python, YAML and Open API
- More than 30 built-in task types
- Supports cluster and Kubernetes deployment
- Includes multiple authentication methods
Against
- Standalone is not intended for production
- Standalone is recommended for fewer than 20 workflows
- In-memory H2 data clears after restart
- Security model assumes a trusted network
The verdict
DolphinScheduler offers visual and code-based workflow orchestration with broad task coverage and self-hosted deployment choices. Production users should favor cluster or Kubernetes setups over the limited standalone mode.
Who it suits
It suits teams building and operating self-hosted data workflows through visual tools or code. Users evaluating standalone deployment should account for its workflow and database limitations.
Plans and prices
Open source
Apache-2.0 software · self-hosted deployment · no paid tier stated
Read 15 Oct 2026 · matca.io
Apache DolphinScheduler
Open-source workflow orchestration platform
Read 9 Oct 2026 · dolphinscheduler.apache.org
On the record
- Access controls
- The security guide describes administrator-managed users, tenants, queues, tokens, worker groups, and authorization for resources and data sources.github.com · read 9 Oct 2026
- API
- The product supports workflow coding and integration through its Open API, and the maker provides a Python API for defining workflows as code.dolphinscheduler.apache.org · read 9 Oct 2026
- Authentication
- Supported login methods are password authentication, LDAP, Casdoor SSO and OAuth2 authorization.github.com · read 15 Oct 2026
- Authorization
- The security center controls queues, tenants, users, alarm groups, worker groups, tokens, projects, resources and data-source permissions.github.com · read 15 Oct 2026
- Backfill
- Complement runs support executing a workflow over a selected date range in serial or parallel mode.dolphinscheduler.apache.org · read 15 Oct 2026
- Community support
- The project directs users and developers to GitHub issues plus users and dev mailing lists for support and discussion.github.com · read 15 Oct 2026
- Concurrency
- The official site claims support for millions of data tasks with high concurrency, throughput and low latency.dolphinscheduler.apache.org · read 15 Oct 2026
- Dependency management
- Workflows can express dependencies across projects and workflows, including dependent and sub-process task nodes.dolphinscheduler.apache.org · read 15 Oct 2026
- Deployment
- The maker documents standalone, cluster, and Kubernetes deployment; standalone is intended for quick evaluation rather than production.github.com · read 9 Oct 2026
- Documentation depth
- Documentation covers installation, architecture, configuration, security, API usage and individual Python task classes with code and YAML examples.dolphinscheduler.apache.org · read 15 Oct 2026
- Execution controls
- Users can kill, pause and resume task or workflow execution.dolphinscheduler.apache.org · read 15 Oct 2026
- Extensibility
- The platform supports custom task types and plugin families for tasks, data sources, storage, alerts and scheduling.github.com · read 15 Oct 2026
- High availability
- The architecture uses decentralized multi-master and multi-worker services so masters and workers can be scaled independently.dolphinscheduler.apache.org · read 15 Oct 2026
- Independent project footprint
- The public repository page shows about 14.5 thousand stars and 5.1 thousand forks.github.com · read 15 Oct 2026
- Latest release
- GitHub lists version 3.4.3 as the latest release, published on September 6, 2026.github.com · read 15 Oct 2026
- License
- The source repositories identify the software as licensed under Apache License 2.0.github.com · read 15 Oct 2026
- Limit: code review workflow
- An independent review says UI-authored DAGs are easy to build but harder to review in pull requests than code-defined pipelines.hysenlabs.com · read 15 Oct 2026
- Limit: failure recovery incident
- A published incident report reproduced a master-crash scenario where restart caused previously unscheduled tasks to run together and potentially exhaust CPU and memory.medium.com · read 15 Oct 2026
