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Hive metastore table access control End of Support

hafeez
New Contributor III

Hello,

We are using Databricks with Hive metastore and not Unity Catalog.

We would like to know if there is any End of Support on Table Access Control with Hive as this link it states that it is legacy.

https://docs.databricks.com/en/data-governance/table-acls/index.html

I understand Databricks recommends Unity Catalog but we want to continue with Hive.

Kindly advice if Hive and Table Access control will be supported with Databricks in the upcoming runtime or we will expect some limitation or EOS.

2 ACCEPTED SOLUTIONS

Accepted Solutions

Kaniz_Fatma
Community Manager
Community Manager

Hi @hafeez, Hive metastore table access control is a legacy data governance model within Databricks.

While it is still available, Databricks strongly recommends using the Unity Catalog instead. The Unity Catalog offers a more straightforward and account-centered governance model. 

However, if you choose to continue using the Hive metastore, here are some important points to consider:

Legacy Model:

  • Hive metastore table access control is regarded as a legacy approach.
  • It provides programmable access control for objects in your workspaceโ€™s Hive metastore from Python and SQL.

Unity Catalog Transition:

  • You can upgrade the tables managed by the Hive metastore to the Unity Catalog metastore.
  • The Unity Catalog provides a more streamlined experience and aligns with Databricksโ€™ recommendations.

End of Support (EOS):

  • Currently, there is no official announcement regarding the end of support for Hive metastore table access control.
  • However, given its legacy status, keeping an eye on Databricks updates and announcements is essential.

Workspace Administrators:

  • Even if table access control is enabled for a cluster, Azure Databricks workspace administrators still have access to file-level data.
  • This is important to consider when managing access permissions.

In summary, while Hive metastore table access control remains functional, transitioning to the Unity Catalog is recommended for a more modern and efficient governance model. 

Keep an eye on Databricks updates for any changes related to support or limitations. ๐Ÿš€

You can refer to the official documentation on this topic for more details.

View solution in original post

hafeez
New Contributor III

Thanks Kaniz, that clears my concerns.

We will do some evaluation on Unity Catalog and follow the upgrade path for it.

View solution in original post

2 REPLIES 2

Kaniz_Fatma
Community Manager
Community Manager

Hi @hafeez, Hive metastore table access control is a legacy data governance model within Databricks.

While it is still available, Databricks strongly recommends using the Unity Catalog instead. The Unity Catalog offers a more straightforward and account-centered governance model. 

However, if you choose to continue using the Hive metastore, here are some important points to consider:

Legacy Model:

  • Hive metastore table access control is regarded as a legacy approach.
  • It provides programmable access control for objects in your workspaceโ€™s Hive metastore from Python and SQL.

Unity Catalog Transition:

  • You can upgrade the tables managed by the Hive metastore to the Unity Catalog metastore.
  • The Unity Catalog provides a more streamlined experience and aligns with Databricksโ€™ recommendations.

End of Support (EOS):

  • Currently, there is no official announcement regarding the end of support for Hive metastore table access control.
  • However, given its legacy status, keeping an eye on Databricks updates and announcements is essential.

Workspace Administrators:

  • Even if table access control is enabled for a cluster, Azure Databricks workspace administrators still have access to file-level data.
  • This is important to consider when managing access permissions.

In summary, while Hive metastore table access control remains functional, transitioning to the Unity Catalog is recommended for a more modern and efficient governance model. 

Keep an eye on Databricks updates for any changes related to support or limitations. ๐Ÿš€

You can refer to the official documentation on this topic for more details.

hafeez
New Contributor III

Thanks Kaniz, that clears my concerns.

We will do some evaluation on Unity Catalog and follow the upgrade path for it.

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