Databricks Unity Catalog Integration Reference
Databricks Unity Catalog allows you to manage and access data in your Databricks account across all of your workspaces and introduces fine-grained access controls in Databricks.
Immuta’s integration with Unity Catalog allows you to manage multiple Databricks workspaces through Unity Catalog while protecting your data with Immuta policies. Instead of manually creating UDFs or granting access to each table in Databricks, you can author your policies in Immuta and have Immuta manage and enforce Unity Catalog access-control policies on your data in Databricks clusters or SQL warehouses:
- Subscription policies: Immuta subscription policies automatically grant and revoke access to Databricks tables.
- Data policies: Immuta data policies enforce row- and column-level security without creating views, so users can query tables as they always have without their workflows being disrupted.
Unity Catalog object model
Unity Catalog uses the following hierarchy of data objects:
- Metastore: Created at the account level and is attached to one or more Databricks workspaces. The metastore contains metadata of all the catalogs, schemas, and tables available to query. All clusters on that workspace use the configured metastore and all workspaces that are configured to use a single metastore share those objects.
- Catalog: A catalog sits on top of schemas (also called databases) and tables to manage permissions across a set of schemas.
- Schema: Organizes tables and views.
- Table: Tables can be managed or external tables.
For details about the Unity Catalog object model, see the Databricks Unity Catalog documentation.
The Databricks Unity Catalog integration supports
- managing and accessing data across multiple Databricks workspaces
- enforcing Unity Catalog row-, column-, and table-level access controls on Databricks clusters and SQL warehouses:
- applying column masking and row-redaction policies on tables
- applying subscription polices on tables and views
- enforcing Unity Catalog access controls, even if Immuta becomes disconnected
- auditing activity of both Immuta users and non-Immuta users
- Delta and Parquet files
- allowing non-Immuta reads and writes
- using Photon
- using a proxy server
Unity Catalog supports managing permissions at the Databricks account level through controls applied directly to objects in the metastore. To interact with the metastore and apply controls to any table, Immuta requires a personal access token (PAT) for an Immuta system account user with permissions to manage all data protected by Immuta. See the permissions requirements section for a list of specific Databricks privileges.
Immuta uses this Immuta system account user to run queries that set up all the tables, user-defined
functions (UDFs), and other data necessary for policy enforcement. Upon enabling the native integration, Immuta
will create a catalog named after your provided
workspaceName that contains two schemas:
immuta_system: Contains internal Immuta data.
immuta_policies: Contains policy UDFs.
When policies require changes to be pushed to Unity Catalog, Immuta updates the internal tables in the
immuta_system schema with the updated policy information. If necessary, new UDFs are pushed to replace
any out-of-date policies in the
immuta_policies schema and any row filters or column masks are
updated to point at the new policies. Many of these operations require compute on the configured Databricks
cluster or SQL endpoint, so compute must be available for these policies to succeed.
Immuta’s Unity Catalog integration applies Databricks table-, row-, and column-level security controls that are enforced natively within Databricks. Immuta's management of these Databricks security controls is automated and ensures that they synchronize with Immuta policy or user entitlement changes.
- Table-level security: Immuta manages REVOKE and GRANT privileges on securable objects in Databricks through subscription policies. When you create a subscription policy in Immuta, Immuta uses the Unity Catalog API to issue GRANTS or REVOKES against the catalog, schema, or table in Databricks for every user affected by that subscription policy.
- Row-level security: Immuta applies SQL UDFs to restrict access to rows for querying users.
- Column-level security: Immuta applies column-mask SQL UDFs to tables for querying users. These column-mask UDFs run for any column that requires masking.
The Unity Catalog integration supports the following policy types:
- Subscription policies
- Select masking policies
- Conditional masking
- Custom masking
- Regex: You
must use the global regex flag (
g) when creating a regex masking policy in this integration. You cannot use the case insensitive regex flag (
i) when creating a regex masking policy in this integration. See the limitations section for examples.
- Rounding (date and numeric rounding)
- Row-level policies
Policy exemption groups
Some users may need to be exempt from masking and row-level policy enforcement. When you add user accounts to the configured exemption group in Databricks, Immuta will not enforce policies for those users. Exemption groups are created when the Unity Catalog integration is configured, and no policies will apply to these users' queries, despite any policies enforced on the tables they query.
The principal used to register data sources in Immuta will be automatically added to this exemption group for that Databricks table. Consequently, users added to this list and used to register data sources in Immuta should be limited to service accounts.
Policy support with
When enabling Unity Catalog support in Immuta, the catalog for all Databricks data sources will be updated
to point at the default
hive_metastore catalog. Internally, Databricks exposes this catalog as a proxy to
the workspace-level Hive metastore that schemas and tables were kept in before Unity Catalog. Since this
catalog is not a real Unity Catalog catalog, it does not support any Unity Catalog policies. Therefore,
Immuta will ignore any data sources in the
hive_metastore in any Databricks Unity Catalog integration,
and policies will not be applied to tables there.
The Databricks Unity Catalog integration supports the access token method to configure the integration and create data sources in Immuta. This is the access token for the Immuta service principal. This service principal must have the metastore privileges listed in the permissions section for the metastore associated with the Databricks workspace. If this token is configured to expire, update this field regularly for the integration to continue to function.
Immuta data sources in Unity Catalog
The Unity Catalog data object model introduces a 3-tiered namespace, as outlined above. Consequently, your Databricks tables registered as data sources in Immuta will reference the catalog, schema (also called a database), and table.
External data connectors and query-federated tables
External data connectors and query-federated tables are preview features in Databricks. See the Databricks documentation for details about the support and limitations of these features before registering them as data sources in the Unity Catalog integration.
Unity Catalog audit
The Databricks Unity Catalog integration audits user queries run in clusters or SQL warehouses for deployments configured with either the Databricks Spark integration with Unity Catalog support or the Databricks Unity Catalog integration. Unity Catalog native audit does not support deployments that use the Databricks Spark integration and the Databricks Unity Catalog integrations simultaneously. See the Unity Catalog native audit page for details.
See the Enable Unity Catalog guide for a list of requirements.
Supported Databricks cluster configurations
The table below outlines the integrations supported for various Databricks cluster configurations. For example, the only integration available to enforce policies on a cluster configured to run on Databricks Runtime 9.1 is the Databricks Spark integration.
|Example cluster||Databricks Runtime||Unity Catalog in Databricks||Databricks Spark integration||Databricks Spark with Unity Catalog support||Databricks Unity Catalog integration|
- The feature or integration is enabled.
- The feature or integration is disabled.
Unity Catalog caveats
- Unity Catalog row- and column-level security controls are unsupported for single-user clusters. See the Databricks documentation for details about this limitation.
- Row access policies with more than 1023 columns are unsupported. This is an underlying limitation of UDFs in Databricks. Immuta will only create row access policies with the minimum number of referenced columns. This limit will therefore apply to the number of columns referenced in the policy and not the total number in the table.
- If you disable table grants, Immuta revokes the grants. Therefore, if users had access to a table before enabling Immuta, they’ll lose access.
You must use the global regex flag (
g) when creating a regex masking policy in this integration, and you cannot use the case insensitive regex flag (
i) when creating a regex masking policy in this integration. See the examples below for guidance:
- regex with a global flag (supported):
- regex without a global flag (unsupported):
- regex with a case insensitive flag (unsupported):
- regex without a case insensitive flag (supported):
- regex with a global flag (supported):
The following features are currently unsupported:
- Databricks change data feed support
- Immuta project equalization and workspaces
- Multiple IAMs on a single cluster
- Column masking policies on views
- Mixing masking policies on the same column
- Row-redaction policies on views
- R and Scala cluster support
- Scratch paths
- User impersonation
- Policy enforcement on raw Spark reads
- Python UDFs for advanced masking functions
- Direct file-to-SQL reads
- Smart order masking
- Date/time and struct columns may cause errors in policy application and should be avoided in column masking policies.
- Snippets for Databricks data sources may be empty in the Immuta UI.
- Some custom WHERE clause policies will cause policy enforcement errors in Unity Catalog. These policies should be avoided if errors occur during policy application.