# Dagster

> Orchestration for data assets

Build, run and observe data pipelines.

- Source: https://github.com/dagster-io/dagster
- Homepage: https://dagster.io
- License: Apache-2.0
- Language: Python
- Stars: 16233
- Forks: 2326
- Contributors: 656
- Last commit: 2026-10-03
- Latest release: 1.13.25 (2026-10-01)
- Purpose: Automation, Data & analytics
- Runs on: Docker / self-host
- For: Enterprise

## Worth score: 77/100

How much DigGitHub recommends it, from activity, adoption, docs, license and security signals.

- Popularity: 21/25
- Momentum: 10/20
- Maintenance: 25/25
- Community: 13/15
- Readiness: 8/15

## Alternatives

- [Apache Airflow](https://diggithub.com/apache/airflow.md): Author, schedule and monitor workflows
- [Kestra](https://diggithub.com/kestra-io/kestra.md): Event-driven orchestration platform
- [Mage](https://diggithub.com/mage-ai/mage-ai.md): Build and run data pipelines
- [Prefect](https://diggithub.com/PrefectHQ/prefect.md): Workflow orchestration for Python
- [Airbyte](https://diggithub.com/airbytehq/airbyte.md): Open-source data movement
- [Apache Superset](https://diggithub.com/apache/superset.md): Enterprise-ready data exploration and visualization
- [Trigger.dev](https://diggithub.com/triggerdotdev/trigger.dev.md): Durable background jobs and AI agents
- [Argo Workflows](https://diggithub.com/argoproj/argo-workflows.md): Workflow engine for Kubernetes

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Source page: https://diggithub.com/dagster-io/dagster
Updated: 2026-10-05