Case Study: HPD Lendscape achieves real-time, scalable factoring performance with Hazelcast

How a FinTech company leveraged in-memory technology to speed up its software offering

HPD Lendscape, a leading secured B2B lending software vendor used by over 140 banks and financial institutions, needed a scalable, low-latency caching solution to support real-time factoring, large multi‑terabyte databases, and cloud readiness as it moved from single‑server Ehcache to multi‑node deployments. The company required high throughput, resilience, and easy integration with its Spring‑based Java platform, so it evaluated several options and selected Hazelcast as the in-memory/data grid solution.

Hazelcast was embedded across Lendscape’s backend services (integrating with Spring and Azul Zulu OpenJDK) to eager‑load static metadata and accelerate access to the core engine and two web front ends, serving data from multi‑terabyte main and much larger reporting databases. As a result, Hazelcast removed database access as the system bottleneck—performance is now hardware‑bound, data access issues have dropped, and the platform processes transactions well within SLAs while enabling realistic soak and performance benchmarking and future cloud, streaming, and ML capabilities.

HPD Lendscape