Case Study: eBay achieves real-time personalized recommendations at massive scale with DataStax Enterprise

eBay Engages Customers with Personalized Recommendations

eBay, the world’s largest online marketplace connecting over 112 million active users with 400+ million items, faced a growing challenge: turning massive, fast-moving structured and unstructured data into real-time, personalized experiences. Traditional relational databases couldn’t scale to meet billions of daily reads and writes or support the rapid analytics needed to surface relevant recommendations and social signals without latency or downtime.

To solve this, eBay deployed DataStax Enterprise powered by Apache Cassandra in a scale-out, multi–data-center architecture with integrated real-time analytics. The platform stores 250+ TB, handles roughly 6 billion writes and 5 billion reads per day, delivers low-latency personalized recommendations and social features (like “like,” “own,” and “want” counts and “Your Favorites”), and maintains high availability with active-active multi–data-center support for continuous uptime and rapid disaster recovery.

eBay