Cloudant’s BigCouch database let the team keep up with a steady flow of data so it could process and analyze it, then share it with the various stakeholders in near-real-time. The team was changing the data about 20 times per day and writing complex workflows to process it, two tasks that fall into BigCouch’s wheelhouse. The database has a built-in MapReduce engine to enable writing and processing the workflows, and it allows for secondary indices, which users can populate with new data from their MapReduce jobs and query very quickly.
This is the first case study I’m reading about BigCouch. But keep in mind that the project initiator is also the founder of Cloudant the company that created and open sourced BigCouch
Original title and link: BigCouch Case Study: Research of Radition in Seattle (NoSQL databases © myNoSQL)