In the NoSQL database space, the key-value store (as opposed to Document, Graph, Object, XML stores) has the strongest reputation for being able to scale out well, providing high throughput writes along with highly concurrent reads. That is possible because of the power in developing the database architecture over a simplistic data model where the key is easily used to hash into a growing number of logical groups (physical nodes).
However, in some cases, that simplistic key-value model could tie your hands when you want to provide a use case that needs a data access pattern involving a range or collections (especially if large) of data. It turns out, this is a fairly common use case pattern showing up in areas of analysis involving time-series, sensor data aggregation, activity grouping, and a whole bunch of use cases where you've got logically related, nested data models.
So, one of the key questions to ask is whether or not your key-value store is providing facilities to help in the implementation of those types of use cases.