Suddenly the data warehousing sector seems to be hotting up. There's EMC's new competency centre and now Kognitio's in-memory data warehouse which threatens to brush server vendors aside if the idea gets adopted big time. How does that one work? The story goes like this: Cluster lots of servers together in a shared-nothing …
Interesting but a bit flawed.
Not really a green solution.
Power and reliability?
This looks like 600 servers with 64GB of memory each. Assuming that these are dual chip machines and with disks and so on then allow say 500W per server (including air-con overheads etc.) That's 300KW (or perhaps £250K per year in electricity at UK prices).
I think I'd ask questions about resilience to. With 600 servers there are going to be lots of failures - software and hardware. Unless this solution is inherently resilient to both, then service levels will be appalling unless the type of access pattern allows for a high degree of data partitioning so that only some queries fail. Duplicating memory is going to be expensive, although I guess that other approaches could be taken.
Personally I would go along with flash being faster, more reliable and much more power efficient. Just to do a rule-of-thumb calculation, 45MBps read flash is available (retail) for about $10 per GB. 40TB of this stuff is approximately $400K. Double it up for reilience and add a bit more for luck and you can have $1TB for $1M. Potential bandwidth is massive as (based on available devices) 40TB would give a theoretical bandwidth of about 12GB per second and you could read the whole lot in about 7 minutes. If the queries don't require every byte to be read you can do better (reading and processing 40TB in a dtabase would take a lot of CPU power).
Of course this is all theory and the hardware and software to connect this many commodity Flash devices is maybe not there, but it does show the potential in the technology.
Incidentally, commodity flash is very poor at random small writes, but the 45MBps devices I refer to can write at that rate sequentially.