tomsoft

-> an ideal use case: capture and store unstructured data, typically tweets. Tweets structure is json based, quite complex with many field and substructure. It's incredibly to store and manipulate such data with Mongodb without even knowing all the details of the fields! It's also a good use case beacause mongodb is fairly good at adding data, pretty bad at deleting data.

same with some others document json oriented database (like elastic search), but mongodb is a good compromise in many area, the query language is easy to understand and powerful, the biggest issue being the diffculty to do complex computation and aggreagation: mapreduce help, aggreagation framework helps too, but in this area SQL is generally much faster for instance.