Two things that are sorely missing in this comparison to NoSql is:
How are they performing horizontal scaling, I'm guessing they aren't, without addressing the issue of sharding and scaling they can't really compare the solution to NoSql - it is the number 1 feature that NoSql has over RDBMS.
If they are achieving 1ms response time , then they almost certainly have the entire table in memory cache.
What happens when the data grows beyond the size of the memory and it's not financially feasible to get a larger memory instance.
1. They probably don't need sharding, since the dataset is small enough to just replicate it in mirrors.
2. 1ms is achievable with SSDs, but 200K q/minute seems slow my gut feeling tells me.
This post is more like "ha we don't need NoSQL for this special use case" - Once you need scaling and some sort of atomics, you quickly have to use HBase for row-level atomicity and scaling.
Redis is probably better suited for the posted usecase anyway.
How are they performing horizontal scaling, I'm guessing they aren't, without addressing the issue of sharding and scaling they can't really compare the solution to NoSql - it is the number 1 feature that NoSql has over RDBMS.
If they are achieving 1ms response time , then they almost certainly have the entire table in memory cache. What happens when the data grows beyond the size of the memory and it's not financially feasible to get a larger memory instance.