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MongoDB as a key-value store MongoDB stores data in collections, which are a group of BSON (Binary JSON) documents where each document is essentially built from a field-value structure.
The difference lies in the way the data is processed; in a key-value store, the data is considered to be inherently opaque to the database, whereas a document-oriented system relies on internal structure in the document in order to extract metadata that the database engine uses for further optimization.
Document databases organize documents into groups called collections, which are analogous to the tables in relational databases. By contrast, key-value databases store all key-value pairs together in a single namespace, which is analogous to a relational schema.
With Cassandra, your data is stored in non-relational partitions just as you insert them—much like any other NoSQL platform would. MongoDB takes the NoSQL concept a step further by being document-based.
A key-value store provides the simplest possible data model and is exactly what the name suggests: it's a storage system that stores values indexed by a key. You're limited to query by key and the values are opaque, the store doesn't know anything about them. This allows very fast read and write operations (a simple disk access) and I see this model as a kind of non volatile cache (i.e. well suited if you need fast accesses by key to long-lived data).
A document-oriented database extends the previous model and values are stored in a structured format (a document, hence the name) that the database can understand. For example, a document could be a blog post and the comments and the tags stored in a denormalized way. Since the data are transparent, the store can do more work (like indexing fields of the document) and you're not limited to query by key. As I hinted, such databases allows to fetch an entire page's data with a single query and are well suited for content oriented applications (which is why big sites like Facebook or Amazon like them).
Other kinds of NoSQL databases include column-oriented stores, graph databases and even object databases. But this goes beyond the question.
Well, I've been investigating NoSQL myself the past month or so. I think it generally could be stated something like
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