Case Study: Shutterfly achieves scalable, cost-effective photo management with MongoDB Atlas on AWS

Shutterfly cuts data infrastructure costs by 20% with MongoDB

Shutterfly, a company that enables millions of people to store and share billions of photos, faced challenges with inflexible and costly-to-scale relational databases. To handle its massive volume of content and improve real-time editing, Shutterfly sought a more efficient data storage solution. This led them to adopt MongoDB, specifically the document database approach of MongoDB Atlas on AWS.

The solution involved migrating Shutterfly's multi-terabyte dataset to MongoDB Atlas using tools like Mongomirror, achieving this with minimal downtime. MongoDB provided the scalable, flexible platform needed to handle thousands of requests per minute and easily scale for seasonal peaks. As a result, Shutterfly gained operational efficiency, faster service launches, and achieved up to a 20% reduction in costs compared to its previous infrastructure.

Shutterfly