Continuous Privacy, Security and Compliance for Databricks environments

Enable consistent governance and security across your ML/AI workloads.

Deep Data Discovery & Classification

Privacera can automatically profile and scan data in AWS S3, Azure Data Lake Store (ADLS) as well as across tables/schema created in Databricks. The files and tables are tagged and the data classification is stored in Privacera catalog.

Access Management - Fine Grained Access Control

Privacera enables column, row and file level access control in Databricks Spark. Privacera leverages Apache Ranger to provide centralized access policies and enforce it across Spark SQL and other workloads in Databricks.


Privacera can help with de-identifying sensitive data with masking or encryption methods. Data could be anonymized before it is stored in the cloud storage. When data is accessed in Databricks or other services, Privacera can dynamically de-anonymize the data based on user level policies.

DataBricks Technology Partner

Fine grain access control - File, column and row level access control in Spark

Deep Data Discovery and Classification for Data Governance

Comply with Privacy and Security regulations such as CCPA, GDPR and others

Balance governance and security imperatives with the need to use data

Privacera integrates seamlessly with Databricks infrastructure and provides continuous security and privacy across the stack

Integrate with Databricks and Cloud services

Privacera discover configuration and natively integrates with Databricks, AWS S3, Azure and other cloud services.

Column, row level Access Control in Spark

Privacera leverages Apache Ranger based plugins to provide column, row and file level access control across Spark functions.

Scan, profile all data in storage and in Databricks

Privacera scans and profiles any new data landing in cloud storage and across databases created in Databricks. Privacera runs on a Databricks cluster and uses rules, machine learning to accurately identify a specific data type and apply tags.

Anonymize and de-anonymize data in Databricks

Privacera can help with privacy and security regulations by anonymizing sensitive data as it is stored in the cloud and accessed using Databricks. The data can be de-anonymized for select users based on a policy.

Frequently asked questions

Does Privacera work with Databricks?

Privacera plugins, based on Apache Ranger, can enforce fine grained access control in Databricks Spark. Privacera plugins are automatically initiated when a Databricks cluster is started.

Does Privacera access management add any performance overhead?

Privacera differs from others solutions that try to manage data requests from Spark and access data on behalf of the Databricks Privacera’s lightweight access enforcement points quickly check a request and let it process if there is policy granting access.

Is Privacera integrated with Hive metadata store and Glue?

Privacera solution can work across any metadata store for Databricks, including Hive Metadata store and Glue. Privacera can enable also tag based access policies based on the data classification.

Get Started Today

Contact us to learn more about Privacera for Databricks and get a FREE risk assessment.