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Dagster

Python orchestrator that models data pipelines as declarative software-defined assets.

Dagster is a data pipeline orchestrator with a declarative programming model, integrated lineage, and observability. Data teams use it to define, schedule, and monitor data assets such as tables, datasets, ML models, and reports across the development lifecycle.

Documented features

• Defines data assets like tables, datasets, ML models, and reports as Python functions
• Schedules asset-producing functions and keeps assets up to date
• Shows asset lineage and dependencies in an interactive web UI
• Runs data quality checks to catch issues and bugs early
• Centralizes metadata with built-in observability, diagnostics, and cataloging
• Supports local development, unit tests, integration tests, staging, and production
• Ships a library of integrations for data stack tools
• Supports CI/CD workflows with reusable components

Feature summaries come from the project's own repository and documentation and describe the software as documented on the verification date, not an evaluation.