Overview
Dagster is a modern data orchestrator built for the cloud era. Unlike task-based orchestrators, Dagster is asset-centric—you define the data assets you want to produce, and Dagster figures out how to build them. It's become the preferred choice for teams moving beyond Airflow.
Key Features
- ✓ Software-Defined Assets: Declare what data you want, not just tasks
- ✓ Type System: Built-in data validation and type checking
- ✓ Integrated Lineage: Automatic dependency tracking
- ✓ Dev Experience: Local development with hot reloading
- ✓ Partitioning: First-class support for time-partitioned data
- ✓ Observability: Built-in metrics, alerts, and freshness tracking
Pros
- 👍 Modern DX—feels like writing application code
- 👍 Asset-centric model matches how teams think about data
- 👍 Excellent testing and local development story
- 👍 Strong dbt integration
- 👍 Active community and rapid development
- 👍 Dagster Cloud is genuinely good
Cons
- 👎 Steeper learning curve than Airflow
- 👎 Smaller ecosystem than Airflow
- 👎 Fewer pre-built integrations
- 👎 Migration from Airflow requires effort
Best For
Teams building new data platforms or ready to move past Airflow's limitations. Especially good for ML pipelines and complex data products.
Founded: 2019 HQ: San Francisco, CA