Case Study: PriceRunner achieves real-time comparison of 100 million offers in milliseconds with GigaSpaces

PriceRunner - Customer Case Study

PriceRunner, a leading shopping comparison site serving 4.4 million monthly visitors across several European markets and ingesting prices from 18,000 merchants, needed to deliver hyper-personalized, real-time price comparisons without delays—especially during seasonal peaks when traffic can spike 20x. The business risk was high: slow pages drive customer abandonment, so PriceRunner required sub-second responsiveness, zero downtime, and real-time analytics across transactional and historical data.

PriceRunner selected the GigaSpaces In‑Memory Computing Platform and a microservices architecture to provide a load‑balanced, elastic in‑memory data grid with event processing and multimodel storage. The deployment enabled updating 100 million prices in parallel while keeping 95th‑percentile response times to 5–8 ms under 20x peak load, maintained continuous availability, integrated with MongoDB/Elasticsearch/Kafka, and unlocked real‑time analytics and ML capabilities for faster feature development and improved customer experience.

PriceRunner