Dagster
Orchestration around data assets rather than tasks.
86
sovereigntyDagster's central idea is that you should declare the tables, models and files you want to exist, and let the system work out what to run — an asset graph instead of a task graph. In practice that means lineage, freshness and data quality are first-class rather than bolted on, and local development and testing are markedly better than Airflow's. The open-source core is Apache-2.0 and complete enough to run production on. Dagster+ is the paid hosted tier; as with Astronomer, be clear about which features live behind it before you build a dependency on them.
OPEN SOURCEApache-2.0 (core; Dagster+ is a paid hosted tier)SELF-HOSTLOCAL-FIRST
LicenseApache-2.0 (core; Dagster+ is a paid hosted tier)
PricingOpen-source core free and self-hostable. Dagster+ is usage-priced with a free trial.
Open sourceYes
Self-hostableYes
Local-first dataYes
What it does well
- +Asset-oriented model matches how data teams actually reason about pipelines
- +Lineage, freshness policies and data quality checks are built in
- +Much better local development and unit-testing story than Airflow
- +Strong typing and explicit IO managers catch errors before production
Where it falls short
- −Smaller ecosystem of integrations than Airflow's provider list
- −The asset mental model is a real relearn if your team thinks in tasks
- −Single-vendor project — governance sits with the company, not a foundation
- −Some operational conveniences are reserved for the paid tier
Dagster as an alternative to
Where Dagster shows up in our comparisons, and how it ranked.
Dagster head-to-head
Straight comparisons against the tools people weigh it against.