Aggregion DataLabs & CleanRoom vs AWS Clean Rooms

Aggregion DataLabs & CleanRoom is an environment for building and running models on data shared by multiple partners. Its workflow spans cataloging, discovering partner datasets, developing models in protected DataLabs, performing CleanRoom calculations, and activating results. Partners connect through a virtual data warehouse, with structured and semi-structured data supported. DataLabs virtual machines depersonalize data and apply distortion models during development. Listed languages include Python, R, PySparc, Scala, and Java. The architecture includes adapters for RDBMS, Hive, and Kafka, plus an advanced integration API. Intel SGX hardware-level encryption is described for enclave memory during shared computations. A decentralized protocol governs metadata, permissions, rights, approvals, and related collaboration actions. Scripts may be reviewed, approved, scheduled, or invoked through API, with execution logs kept on an immutable ledger. Deployment can be cloud or on-premise, and customers choose hosting for the DataLab and enclave. Pricing is available on request.

AWS Clean Rooms lets companies analyze collective datasets without exchanging or copying the underlying data. Multiple companies can contribute to one collaboration while retaining data in their own accounts. Customers can permission AWS data and work with partner datasets in Snowflake and AWS through zero-ETL. Analysis supports SQL, Spark SQL, PySpark and machine learning. AWS lists advertising insights, investment decisions, research and development, customer insights and reporting as use cases. Privacy controls include fine-grained analysis rules, differential privacy, cryptographic computing, output restrictions and query logging. Clean Rooms ML supports custom and lookalike modeling; custom modeling allows collaborators to bring a model for training and inference without sharing underlying data or intellectual property. Access is available through the console, API, SDKs and command line. AWS lists availability in 11 Regions. Pricing is pay-as-you-go by capability and Region, with stated minimum charges for Spark SQL and PySpark. No free plan is available.