Your partition keys can be composite, have a look here:
I agree with your other pain points - in terms of not being able to get counts, secondary indices etc. However, you can easily simulate some of those - maintain your own summary tables, indices and so on. These ought to emerge as platform features pretty soon though. It's not perfect, but its feature set is close to Dynamo.
As for Mongo DB, I guess this service has been built from ground-up to provide the availability guarantees and automatic partition management features. I don't know if Mongo provides those. You could run Mongo yourself on Azure if you wanted to; there's even a supported solution done recently.
• They both are NoSQL schema-less table stores, where a table can store entities with completely different properties
• They have a two attribute (property) composite primary key.One property that is used for partitioning and the other property is for optimizing range based operations within a partition
• Both of them have just a single index based on their composite primary key
• Both are built for effectively unlimited table size, seamlessly auto scale out with hands off management
• Similar CRUD operations
How Windows Azure Tables is implemented can be found in this SOSP paper and talk:
As mentioned by someone else, one difference is that DynamoDB stores its data completely in SSDs, whereas, in Azure Storage our writes are committed via journaling (to either SSD or a dedicated journal drive) and reads are served from disks or memory if the data page is cached in memory. Therefore, the latency for single entity small writes are typically below 10ms due to our journaling approach (described in the above SOSP paper). Then single entity read times for small entities are typically under 40ms, which is shown in the results here:
Once and awhile we see someone saying that they see 100+ms latencies for small single entity reads and that is usually because they need to turn Nagle off, as described here: