Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Dagster is a data orchestration platform designed to manage the entire lifecycle of data assets through declarative modeling and version-controlled code. It functions as a workflow engine that treats data assets as first-class primitives, allowing teams to define, schedule, and monitor complex pipelines while maintaining clear visibility into lineage, dependencies, and data quality. The platform distinguishes itself by using a code-as-configuration framework that enables standard software engineering practices, such as unit testing and local mocking, to be applied directly to data workflows.