Case Study: a large retailer achieves near-real-time customer identity resolution with TigerGraph

Large Retailer tests 6K–7K QPS identity upserts with TigerGraph

A large retailer needed to modernize its customer identity resolution from a batch-driven process into a near-real-time OLTP identity graph. The challenge was to support high-volume ingestion and reliably link customer data points like accounts, devices, and emails as events arrived, all while ensuring production readiness at a multi-terabyte scale for downstream systems.

TigerGraph helped the large retailer design and implement a graph-native solution. This provided a path to drastically reduce identity resolution lag and improve data freshness, with tested upsert throughput reaching 6K–7K QPS. The solution also established a production-grade foundation for future use cases in fraud and personalization, addressing key requirements for monitoring, disaster recovery, and high availability.