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Guides#

Dagster Guides#

This section explains how to accomplish common tasks in Dagster and showcases Dagaster's experimental features.

NameDescription
Versioning and MemoizationThis guide describes how to use Dagster's versioning and memoization features. Experimental
LakehouseThis guide describes how to use Dagster Lakehouse. Experimental
Lakehouse with Pandas and PySparkThis guide describes how to use Dagster Lakehouse with Pandas and PySpark. Experimental

Integration Guides#

This section includes guides on how to use Dagster with other tools.

NameDescription
Dagster with dbtThis guide shows how to orchestrate dbt from Dagster.
Dagster with AirflowThis guide shows how to compile an Airflow DAG into a Dagster pipeline.
Dagster with Great ExpectationsThis guide shows how to run data quality tests using Great Expectations in a Dagster pipeline.
Dagster with PySparkThis guide shows how to define and execute spark jobs in Dagster.
Dagster with PandasThis guide shows how Dagster works with Pandas.
Dagster with Jupyter/PapermillThis guide shows how to orchestrate Jupyter notebooks from Dagster.