We've moved some of our data we used to store in Postgresql and Memcached into Redis. Key value stores are much better suited for storing hierarchical object data. You can store blob data much faster and with much less development time and effort than using an ORM to map your blob to a RDBMS.
I have an open source c# redis client that lets you store and retrieve any POCO objects with 1 line:
var customers = redis.Lists["customers"]; //Implements IList<Customer>
customers.Add(new Customer { Name = "Mr Customer" });
Key value stores are also much easier to 'scale-out' as you can add a new server and then partition your load evenly to include the new server. Importantly, there is no central server that will limit your scalability. (though you will still need a strategy for consistent hashing to distribute your requests).
I consider Redis to be a 'managed text file' on steroids that provides fast, concurrent and atomic access for multiple clients, so anything I used to use a text file or embedded database for I now use Redis. e.g. To get a real-time combined rolling error log for all our services (which has notoriously been a hard task for us), is now accomplished with only a couple of lines by just pre-pending the error to a Redis server side list and then trimming the list so only the last 1000 are kept, e.g:
var errors = redis.List["combined:errors"];
errors.Insert(0, new Error { Name = ex.GetType().Name, Message = ex.Message, StackTrace = ex.StackTrace});
redis.TrimList(errors, 1000);
