Please allow the possibility that Redis can be improved and should be improved. Otherwise other systems will eventually take its market apart.
I appreciate your comments very much. I've wrote about you in my blog. I am an engineer and I disagree with some of the design decisions that were made in Redis and I decided to do something about it :) to your points:
1. DF provides full compatibility with single node Redis while running on all cores, compared to Redis cluster that can not provide multi-key operations across slots.
2. Much stronger point - we provide much simpler system since you do not need to manage k processes, you do not need to *provision* k capacities that managed independently within each process and you do not need to monitor those processes, load/save k snapshots etc. Our snapshotting is point in time on all cores.
3. Due to pooling of resources DF is more cost efficient. It's more versatile. We have a design partner that could reduce its costs by factor of 3 just because he could use x2gd machine with extra high memory configuration.
Regarding your note about memcached - while we provide similar performance like memcached our product proposition is anything unlike memcached and it's more similar to Redis. Having said that - I will add comparison to memcached. I do believe that memcached as performant as DF because essentially it's just an epoll loop over multiple threads.
Re you comment about snapshotting. We also push the data into serialization sink upon write, hence we do not need to aggregate changes until the snapshot completes. The complex part is to ensure that no key is written twice and that we ensure with versioning. I do agree that there can be extreme cases where we need to duplicate memory usage for some entries but it's only for the entries at flight - those that are being processed for serialization.
Update: re versioning and memory efficiency. We use DashTable that is more memory efficient that Redis-Dict. In addition, DashTable has a concept of bucket that is comprised of multiple slots (14 in our implementation). We maintain a single 64bit version per bucket and we serialize all the entries in the bucket at once. Naturally, it reduces the overhead of keeping versions. Overall, for small value workloads we are 30-40% more efficient in memory than Redis.