Using MongoDB as a low-latency, high-throughput key-value store for financial market data (or any other domain specific data).
By compressing and chunking data you can easily build a versioned key-value store using Mongo. This store outperforms significantly more expensive data platforms, and scales to terabytes of data.
Storing data denormalized in a key-value store reduces the burden of storage and retrieval, and allows applications to access, update and store data in its natural shape. The result is a system that can both ship data at high throughput to a cluster of machines for batch processing, as well as provide low latency to interactive users.