Clean Rooms

Bringing real-time fraud prevention to government benefits

Databricks is helping federal agencies move fraud detection for benefit programs from after-the-fact reviews to real time, building on techniques honed with banks, credit card companies, and insurers. With over 80% of federal executive departments already on the platform, tools like OpenSharing and Clean Rooms let agencies share fraud signals across silos without exposing raw data, surfacing schemes no single agency could catch alone.

This release updates account and workspace IAM v2 API method paths (breaking change), modifies the internal_id field type to string, and removes code_source_path from AiRuntimeTask. New features include clean room task management, postgres federation configuration, enhanced ML streaming capabilities, and additional pipeline connector options.

This release introduces a breaking change by removing the codeSourcePath field from AiRuntimeTask in the Jobs API. Additional updates include support for Clean Room JAR analysis and task run listings, a JDBC connection type for

This release adds SDK support for JAR analysis assets, review workflows, and task run listing in Databricks Clean Rooms, alongside a new JDBC connection type for catalog integrations. Additional updates introduce Azure capacity reservation group settings for compute instance pools, initial parent paths for bundle deployments, and lifetime attributes for ML time windows.

Clean Rooms API support in the Go SDK now includes fields for shared output configuration, notebook asset metadata, and collaborator aliases. Pipeline options for Google Ads, Meta Marketing, and TikTok Ads connectors now support custom

This release adds shared output options, notebook metadata, and collaborator alias fields to the Clean Rooms Java SDK. It also introduces custom report options for Google Ads, Meta Marketing, and TikTok Ads ingestion pipelines.

How Stagwell built privacy-safe ID matching on Databricks

Stagwell built a privacy-safe ID matching solution on Databricks, leveraging Databricks Clean Rooms and Marketplace apps to securely match first-party data with identity graphs. This enables brands to create actionable audiences without exposing sensitive information or raw records.