Different NoSQL solutions solve different problems for different uses - so first off the best thing to do is look at your problem and break it down
- You are writing heavily to storage, therefore write speed is important to you
- You want to perform aggregation operations on that data and have the results of that easily queryable
- Read speed isn't that important from the sound of things, at least not in an "web application has to be really responsive for millions of people" kind of way
- I don't know if you need dynamic queries or not
Let's look at Couch, Mongo and Raven in a very high level, generalised way
Raven
- Fast writes
- Fast queries (eventually consistent, pre-computed, aggregation via map/reduce)
- Dynamic queries possible, but not really appropriate to your use case, as you're most likely going to be querying by date etc
Mongo
- Blindingly Fast writes (In my opinion dangerously, because power going off means losing data ;-))
- Slow reads (relatively), aggregation via map/reduce, not pre-computed
- Dynamic queries are just what_you_do, but you probably have to define indexes on your columns if you want any sort of performance on this sort of data
Couch
- Fast writes
- Fast-ish reads (Pre-computed, but updated only when you read (IIRC)
- Dynamic queries not possible, all pre-defined via map or map/reduce functions
So, basically - do you need dynamic queries over this sort of data? Is the read speed incredibly important to you? If you need dynamic queries then you'll want Raven or Mongo (For this sort of thing Couch is probably not what you are looking for anyway).
FWIW, Mongo's only use case in my opinion IS for logging, so you might have an anwer there.
