DagsterDocs
Guides#
Dagster Guides#
This section explains how to accomplish common tasks in Dagster and showcases Dagaster's experimental features.
| Name | Description |
|---|---|
| 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 |
Integration Guides#
This section includes guides on how to use Dagster with other tools.
| Name | Description |
|---|---|
| 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. |