Case Study: Euclid achieves rapid, large-scale analytics and 80–90% cost savings with Amazon Web Services

Euclid - Customer Case Study

Euclid is a Palo Alto–based startup that helps brick-and-mortar retailers optimize marketing, merchandising, and operations by measuring foot traffic and customer behavior across nearly 400 locations, covering about 21 million shopping sessions per month. The analytics team runs SQL queries, develops new heuristics, and sometimes must re-compute up to 18 months of historical data, creating large, unpredictable compute spikes and a need for a flexible, scalable environment.

Euclid uses AWS (with a Heroku web layer) — storing data on Amazon S3, processing with Amazon EMR and EC2, and running analytics on Amazon Redshift. Moving from MySQL to Redshift cut a simple row-count query from 5.5 hours to 30 seconds and reduced database costs by about 90%; EMR eliminated cluster management for Hadoop jobs. The stack lets Euclid store ~30 GB/day, run complex queries on tens of terabytes in hours rather than weeks, and achieve overall infrastructure savings of 80–90%, enabling rapid experimentation and growth.

Euclid

Ken Leung

Co-Founder and CTO