Case Study: The New York Times achieves agile, scalable real-time social analytics with MongoDB

The New York Times Runs MongoDB

The New York Times Research & Development team needed a way to capture and analyze fast-changing social-data around its content (Project Cascade) — answering questions like when to tweet and which stories spark engagement. Traditional relational databases made iterative changes and evolving data models costly and slow, while the volume and velocity of Twitter and click data meant the system had to scale quickly.

The team adopted MongoDB for its flexible, schema-less model and ease of prototyping: they started on a single node (generating ~100 GB/month early on) and moved to a four-node replica set as demand grew. MongoDB enabled real-time processing of ~100,000 tweets per day, rapid iteration on data models without upfront schema design, and a scalable path forward — a pattern later echoed by other publishers such as The Guardian.

The New York Times

Jake Porway

Data scientist