Uploaded June 2026 | Updated September 2026, 3 weeks ago
Architecting Scalable Data Lineage Graph for Privacy Compliance and Agentic Analysis
Maharshi Jha and Aygun Aydin, Meta
Privacy compliance demands granular, real-time tracking of data flows at scale. This talk presents the architecture behind Meta's in-memory lineage graph, processing billions of edges across web, warehouse, and AI systems. We cover compressed graph storage, efficient traversal algorithms, and cross-platform data flow mapping. Beyond compliance, we explore how the same architecture enables agentic analysis through interactive graph traversals. The presentation shares practical solutions and architectural lessons from operating at billion-edge scale daily.
View the full PEPR '26 program at usenix.org/conference/pepr26/program
Architecting Scalable Data Lineage Graph for Privacy Compliance and Agentic Analysis
Maharshi Jha and Aygun Aydin, Meta
Privacy compliance demands granular, real-time tracking of data flows at scale. This talk presents the architecture behind Meta's in-memory lineage graph, processing billions of edges across web, warehouse, and AI systems. We cover compressed graph storage, efficient traversal algorithms, and cross-platform data flow mapping. Beyond compliance, we explore how the same architecture enables agentic analysis through interactive graph traversals. The presentation shares practical solutions and architectural lessons from operating at billion-edge scale daily.
View the full PEPR '26 program at usenix.org/conference/pepr26/program
