BNP Paribas cuts database size and maintenance time by more than half.
This case example is a great start on providing real-world evidence of the capabilities of Exadata V2. The detail here is much more meaningful to any potential customer than abstract TPC-H benchmarks or Exadata sales pipeline figures.
BNP Paribas isn't the largest deployment I'll cover in my upcoming Big Data story (that title goes to Catalina Marketing with 2.5 petabytes in Netezza). But as Duffy points out, Exadata V2's compression capabilities have cut a 23-terabyte database down to less than half that size.
Ironically, size isn't necessarily the best gauge of database "scalability." Column-store database vendors such as Sybase, Vertica and ParAccel will tell you they have to educate some customers about the deceivingly small size of their deployments. If your DBMS can compress a 100-terabyte store down to 10 terabytes, as these vendors say they can do, you won't win a my-database-is-bigger-than-yours contest. But you will save on storage costs and more.
As far as performance gains go, I've heard some very impressive reports in recent weeks. Catalina Marketing says it has cut model-scoring times from 4.5 hours down to 60 seconds by taking SAS code into the Netezza database. Cabela's says it's now handing SAS queries inside Teradata in about hour that used to take four days to prepare and run with a conventional data warehouse and separate SAS data sets.
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You can't make apples-to-apples comparisons between these results and the 16X-to-17X average improvement that BNP Paribas reports. And, as Duffy says, he has hardly had time to learn how to get the most out of Exadata.
Oracle customers take heart. Real-world deployment references for Exadata V2 are emerging. Your best bet is to read about reference customers, find those that are most similar to your operation and see if you can talk to the people, like Jim Duffy, who manage those deployments.
Don't stop there. When you're a serious buyer looking to drop six, seven or even eight figures, you have every right to ask for a pilot test with your sample data and queries. Not every vendor will oblige, but then, you don't have to consider every vendor.
Ten years ago it was pretty much a three-horse race when it came to large-scale data warehousing -- Oracle, IBM, Teradata. Microsoft is about to enter that ring, and today there are at least six other credible vendors as well as emerging open-source options. Viva la choice.
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