Hudl, a sports software startup, is using MongoDB as the data store for its online video analysis platform.
The platform, used by coaches, athletes and recruiters, offers access to video analysis tools from any computer or mobile device. The MongoDB-based platform makes it easy to upload, sort, analyze and share video to help coaches learn about their teams, scout opponents and win.
After reaching the limits of what SQL was able to deliver, Hudl turned to MongoDB for video metadata storage.
MongoDB delivers a flexible data model, ensuring coaches are not restricted when defining variable data, such as football formations, camera angles, and custom notes used for post-game analysis. With MongoDB, Hudl can create a single collection with high-speed querying, while easily and cost-effectively sharding to scale linearly.
Brian Kaiser, CTO at Hudl, said: “MongoDB makes it so easy to add shards that we don’t require a large capital expenditure to upgrade, which is great from a predictability point of view. Together with Amazon’s Provisioned IOPS, MongoDB delivers remarkably stable query.”
MongoDB has increased developer productivity by facilitating Hudl’s A/B testing and enabling the incremental, easy rollout of new features. In addition, Hudl relies on MongoDB Management Service (MMS) as a crucial asset to monitor MongoDB clusters and proactively address issues.