You can use Databricks Connector on the Windows and Linux operating systems and create a Databricks connection to connect to Databricks endpoints hosted on Amazon Web Services, Microsoft Azure environment, and Google Cloud Platform.

When you read data from and write data to Databricks, you can stage the data in Amazon Web Services, Microsoft Azure environment, or in a volume in Databricks.

To connect to Databricks endpoints hosted on Google Cloud Platform, you need to stage the data in Databricks Volumes.

You can use Delta UniForm to read Delta tables formatted for Apache Iceberg. When you use Delta UniForm, Databricks automatically creates the necessary Iceberg metadata files in the background that enables Iceberg clients to read Delta tables without rewriting data.

You can read from and write to Unity Catalog-managed Apache Iceberg tables in a mapping.

Unity Catalog-managed Apache Iceberg tables don't apply to mappings in advanced mode.

You can read data from views and materialized views in Databricks.

Views and materialized views don't apply to mappings in advanced mode.

For Linux operating systems, you can switch mappings to advanced mode to include transformations and functions that enable advanced functionality. A mapping in advanced mode can run on the

advanced cluster

hosted on Amazon Web Services, Microsoft Azure environment, or on a self-service cluster.