Scaling Social Ecommerce Architecture Case study

A recent study showed that over 92 percent of executives from leading retailers are focusing their marketing efforts on Facebook and subsequent applications. Furthermore, over 71 percent of users have confirmed they are more likely to make a purchase after “liking” a brand they find online. (source


Sears Architect Tomer Gabel provides an insightful overview on how they built a Social Ecommerce solution for that can handle complex relationship quires in real time. Tomer goes through:

  • the architectural considerations behind their solution
  • why they chose memory over disk
  • how they partitioned the data to gain scalability
  • why they chose to execute code with the data using GigaSpaces Map/Reduce execution framework
  • how they integrated with Facebook
  • why they chose GigaSpaces over Coherence and Terracotta for in-memory caching and scale

In this post I tried to summarize the main takeaway from the interview.

You can also watch the full interview (highly recomended).

Read the full story here