February 2021

These features and Databricks platform improvements were released in February 2021.

Note

Releases are staged. Your Databricks account may not be updated until a week or more after the initial release date.

New Databricks Power BI connector (GA)

February 26, 2021

The new Power BI connector for Azure Databricks, released in public preview in September 2020, is now GA. It provides:

• Simple connection configuration: the new Power BI Databricks connector is integrated into Power BI, and you configure it using a simple dialog with a couple of clicks.

• Faster imports and optimized metadata calls, thanks to the new Databricks ODBC driver, which comes with significant performance improvements.

• Access to Databricks data through Power BI respects Databricks table access control.

For more information, see Connect Power BI to Databricks.

Databricks on Google Cloud public preview

February 17, 2021

Databricks is pleased to announced the public preview of Databricks on Google Cloud, which brings deep integration with Google Cloud technologies and billing. For access, contact your Databricks account team.

Google Cloud technology integration

Databricks on Google Cloud runs on Google Kubernetes Engine (GKE) and provides a built-in integration with Google Cloud technologies:

• Google Cloud Identity: Databricks workspace users can authenticate with their Google Cloud Identity account (or GSuite account) using Google’s OAuth 2.0 implementation, which conforms to the OpenID Connect spec and is OpenID certified.

• Google Cloud Storage: Databricks notebooks can use Google Cloud Storage (GCS) buckets as data sources:

  • Access GCS buckets as DBFS mounts: You can create Databricks File System (DBFS) mounts. See Access a GCS bucket through DBFS.

    Note

    DBFS access to the local file system (FUSE mount) is not supported in this release. For DBFS access, the Databricks dbutils commands, Hadoop Filesystem APIs such as the %fs command, and Spark read/write APIs are available.

  • Access GCS buckets directly: You can use gs:/ paths directly in notebooks. See Access a GCS bucket directly with a Google Cloud service account key.

• BigQuery: Databricks on Google Cloud notebooks can read and write to BigQuery as a data source.

Initial account setup

To learn how to set up your Databricks on Google Cloud account and create your first Databricks workspace, see Get started: Account and workspace setup.

What’s in this release?

Some features available in Databricks on other clouds are not available in Databricks on Google Cloud as of this release. For a list of supported and unsupported features, see Databricks on Google Cloud features.

Known issues

For a list of known issues in the current release, see Known issues.