Dagu vs Kestra
| Tagline | DAG-based workflow orchestrator with a web UI — cron replacement with real dependencies | Event-driven orchestration platform for scheduled and API-triggered workflows |
| Category | Automation & iPaaS | Automation & iPaaS |
| Replaces | Zapier, Make, Tray.io | Zapier, Workato |
| GitHub stars | 3.5k | 27k |
| Language | Go | Java |
| License | GPL-3.0 | Apache-2.0 |
| Self-host difficulty | 2/5 Easy | 3/5 Moderate |
| Deploy options | Docker Manual | Docker Docker Compose Kubernetes Manual |
| Managed hosting | ||
| Last updated | today | today |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Dagu
- No distributed worker pool — all steps run on the same host, limiting horizontal scale
- No built-in secrets vault; credentials must be managed via environment variables or external tools
- UI is functional but lacks advanced features like parameterized run forms or dynamic DAG generation
- Community is smaller than Airflow or Prefect; fewer integrations and plugins
Kestra
- YAML-declarative workflows are more engineering-oriented than no-code Zapier flows.
- Enterprise edition gates SSO, RBAC, multi-tenancy, audit logs, and worker isolation.
- Connectors are plugins focused on data/infra systems rather than consumer SaaS apps.
- Production self-hosting benefits from Postgres plus a queue, raising operational overhead.
Bottom line
Choose Dagu if you want the lower-effort setup; choose Kestra for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.