LiveRamp Clean Room — Architecture at Terabyte Scale
LiveRamp's clean room architecture runs at terabyte scale on Kubernetes with dynamic Spark workloads, using differential privacy to enable cross-publisher data matching without raw list sharing.
Scale
Terabytes of data, hundreds of queries/hour, billions of rows per query
Before
No privacy-safe mechanism for cross-publisher data matching without sharing raw customer lists
After
Data plane on Kubernetes (EKS/AKS/GKE) with dynamically scaled Apache Spark, differential privacy + aggregation thresholds
Key Insight
The clean room pattern solves 'I want to match my customer list with your customer list without sharing the lists.' Differential privacy is what makes it legally and contractually defensible.
In a Snowflake Conversation
The clean room pattern solves the 'I want to match my customer list with your customer list without sharing the lists' problem. Differential privacy is what makes it legally and contractually defensible.
My Read
Practitioner commentary coming soon.
Relevant Conversations