Case Study: Foursquare achieves scalable check-in growth and faster development with MongoDB

Foursquare - Customer Case Study

Foursquare, the location-based social network, experienced rapid growth in users and activity that began to overwhelm its original single relational database. With limited engineering resources and an ever-growing check-in dataset that would soon exceed a single machine, the company needed a scalable, maintainable platform to support continued expansion and agile development.

Foursquare migrated venues and check-ins to MongoDB, leveraging its built-in auto-sharding to partition data, scale writes, and add nodes without building a custom sharding layer. The switch simplified the data model (for example, embedding tags directly in venue documents), improved runtime efficiency, and allowed engineers to focus on product work while supporting large-scale growth.

Foursquare

Harry Heymann

Lead Server Engineer, Foursquare