# Databricks

Databricks is a cloud-based platform for big data processing.

Tonic Structural can run Spark jobs on Databricks on AWS and Azure Databricks.

<table data-view="cards"><thead><tr><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Structural process for Databricks</strong><br><br>How Structural generates output from Databricks.</td><td><a href="databricks/connectors-databricks-process-overview">connectors-databricks-process-overview</a></td></tr><tr><td><strong>System requirements</strong><br><br>Supported versions and providers.<br><br></td><td><a href="databricks/databricks-system-requirements">databricks-system-requirements</a></td></tr><tr><td><strong>Structural differences and limitations</strong><br><br>Features that are unavailable or work differently with the Databricks connector.</td><td><a href="databricks/databricks-tonic-differences">databricks-tonic-differences</a></td></tr><tr><td><strong>Required Databricks configuration</strong><br><br>Required configuration for Databricks before you create a Structural workspace.</td><td><a href="databricks/before-you-create-a-databricks-workspace">before-you-create-a-databricks-workspace</a></td></tr><tr><td><strong>Configure workspace data connections</strong><br><br>Connecting to the source and destination for a Databricks workspace.</td><td><a href="databricks/connecting-to-databricks">connecting-to-databricks</a></td></tr><tr><td><strong>Databricks connection troubleshooting</strong><br><br>Options for self-hosted instances to troubleshoot connection failures.</td><td><a href="databricks/databricks-connection-troubleshooting">databricks-connection-troubleshooting</a></td></tr></tbody></table>


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