This section explains how to accomplish common tasks in Dagster and showcases Dagaster's experimental features.
Name | Description |
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Versioning and Memoization | This guide describes how to use Dagster's versioning and memoization features. Experimental |
Lakehouse | This guide describes how to use Dagster Lakehouse. Experimental |
Lakehouse with Pandas and PySpark | This guide describes how to use Dagster Lakehouse with Pandas and PySpark. Experimental |
This section includes guides on how to use Dagster with other tools.
Name | Description |
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Dagster with dbt | This guide shows how to orchestrate dbt from Dagster. |
Dagster with Airflow | This guide shows how to compile an Airflow DAG into a Dagster pipeline. |
Dagster with Great Expectations | This guide shows how to run data quality tests using Great Expectations in a Dagster pipeline. |
Dagster with PySpark | This guide shows how to define and execute spark jobs in Dagster. |
Dagster with Pandas | This guide shows how Dagster works with Pandas. |
Dagster with Jupyter/Papermill | This guide shows how to orchestrate Jupyter notebooks from Dagster. |