@What do they add...
I argue ("that's not fair") that you had to be adding more, hence my question. I don't think you've answered it though. Step by step:;;
> Well, try an optimiser that almost always come up with an excellent query plan, no matter how complex the SQL...that's MUCH harder than it sounds.
* I know how hard it is, and in general it's totally impossible. I can give you simple sql that I'm sure you cannot automatically optimise (I discussed the example in email with Hugh Darwen and he agreed). And if by some magic you could, I guarantee I could find you one you could not. And it would not be large either.
But from experience I know MSSQL can produce excellent query plans for some of the most horrid SQL I've ever seen. So buy MSSQL and drop it onto your stock hardware. NB. I don't work for MS.
> Try unconditional intra-node parallelism - 10 or 12 virtual processors, each owning a virtual disk, running on a single SMP node to tackle each query in parallel.
* Why not use real processors? Why virtualise the disk - all you risk getting is simultaneous reads fighting each other for access to the real disk. At that price you could use real processors each running a disk cluster. In other words, a roomful of bog-standard servers.
And MSSQL can run nicely on an SMP multiprocessor, doling out work to each core as necessary.
> Try automatic table space management, no matter how big the system.
* yeah right. Big DBs need big management. You may provide remote DBA time as part of the package, but that's not quite what you've described.
> Try linear scalability, certified to >1,000 SMP nodes.
* WTF are you doing with that much processing power? And how much would it cost? and how many big (yet bog-standard servers) could you buy and shove in a big room for the price you quote?
> Big banks, telcos and retailers have been using Teradata for decades because "it just works".
* hmmm. And again hmmmmm. Given how brilliantly bankers have recently proven to manage trillions of pounds of assets, says loads for their judgement.
But these days you can buy *big* stock hardware and run big DBs on it, with (what I understand to be) decent analysis tools. And analysis of data warehouses tends to be on large static snapshots, so it can be distributed freely, usually nightly after updating, and processed by multiple different boxes simultaneously. So what are you offering?
I'm afraid you haven't answered my question. And I'm not trying to be destructive, I'd really like to know.