February 25, 2009

Even more final version of my TDWI slide deck

My TDWI talk on How to Select an Analytic DBMS starts in less than an hour.  So the latest version of my slide deck should prove truly final, unlike my prior two.

I won’t have printouts or other access to my notes, so those aren’t a good guide to the actual verbiage I’ll use.

February 25, 2009

Partial overview of Ab Initio Software

Ab Initio is an absurdly secretive company, as per a couple of prior posts and the comment threads on same. But yesterday at TDWI I actually found civil people staffing an Ab Initio trade show booth. Based on that conversation and other tidbits, I think it’s fairly safe to say: Read more

February 23, 2009

MapReduce user eHarmony chose Netezza over Aster or Greenplum

Depending on which IDG reporter you believe, eHarmony has either 4 TB of data or more than 12 TB, stored in Oracle but now analyzed on Netezza.  Interestingly, eHarmony is a Hadoop/MapReduce shop, but chose Netezza over Aster Data or Greenplum even so.  Price was apparently an important aspect of the purchase decision. Netezza also seems to have had a very smooth POC. Read more

February 18, 2009

The Netezza guys propose a POC checklist

The Netezza guys at “Data Liberators” are being a bit too cute in talking about FULL DISCLOSURE yet not actually saying they’re from Netezza — but only a bit, in that their identity is pretty clear even so.  That said, they’ve proposed a not-terrible checklist of how to conduct POCs.  Of course, vendor-provided as it is, it’s incomplete; e.g., there’s no real mention of a baseball-bat test.

Here’s the first part of the Netezza list, with my comments interspersed. Read more

February 1, 2009

Oracle says they do onsite Exadata POCs after all

When I first asked Oracle about Netezza’s claim that Oracle doesn’t do onsite Exadata POCs, they blew off the question. Then I showed Oracle an article draft saying they don’t do onsite Exadata proofs-of-concept. At that point, Oracle denied Netezza’s claim, and told me there indeed have been onsite Exadata POCs.  Oracle has not yet been able to provide me with any actual examples of same, but perhaps that will change soon.  In the mean time, I continue with the assumption that Oracle is, at best, reluctant to do Exadata POCs at customer sites.

I do understand multiple reasons for vendors to prefer POCs be done on their own sites, both innocent (cost) and nefarious (excessive degrees of control). Read more

January 15, 2009

Netezza’s marketing goes retro again

Netezza loves retro images in its marketing, such as classic rock lyrics, or psychedelic paint jobs on its SPUs.  (Given the age demographics at, say, a Teradata or Netezza user conference, this isn’t as nutty as it first sounds.) Netezza’s latest is a creative peoples-liberation/revolution riff, under the name Data Liberators.  The ambience of that site and especially its first download should seem instinctively familiar to anybody who recalls the Symbionese Liberation Army when it was active, or who has ever participated in a chant of “The People, United, Will Never Be Defeated!”

The substance of the first “pamphlet”, so far as I can make out, is that you should only trust vendors who do short, onsite POCs, and Oracle may not do those for Exadata. Read more

January 4, 2009

Expressor pre-announces a data loading benchmark leapfrog

Expressor Software plans to blow the Vertica/Syncsort “benchmark” out of the water, to wit

What I know already is that our numbers will between 7 and 8 min to load one TB of data and will set another world record for the tpc-h benchmark.

The whole blog post has a delightful air of skepticism, e.g.:

Sometimes the mention of a join and lookup are documented but why? If the files are load ready what is there to join or lookup?

… If the files are load ready and the bulk load interface is used, what exactly is done with the DI product?

My guess… nothing.

…  But what I can’t figure out is what is so complex about this test in the first place?

December 14, 2008

The “baseball bat” test for analytic DBMS and data warehouse appliances

More and more, I’m hearing about reliability, resilience, and uptime as criteria for choosing among data warehouse appliances and analytic DBMS. Possible reasons include:

The truth probably lies in a combination of all these factors.

Making the most fuss on the subject is probably Aster Data, who like to talk at length both about mission-critical data warehouse applications and Aster’s approach to making them robust. But I’m also hearing from multiple vendors that proofs-of-concept now regularly include stress tests against failure, in what can be – and indeed has been – called the “baseball bat” test. Prospects are encouraged to go on a rampage, pulling out boards, disk drives, switches, power cables, and almost anything else their devious minds can come up with to cause computer carnage. Read more

December 2, 2008

Data warehouse load speeds in the spotlight

Syncsort and Vertica combined to devise and run a benchmark in which a data warehouse got loaded at 5 ½ terabytes per hour, which is several times faster than the figures used in any other vendors’ similar press releases in the past. Takeaways include:

The latter is unsurprising. Back in February, I wrote at length about how Vertica makes rapid columnar updates. I don’t have a lot of subsequent new detail, but it made sense then and now. Read more

November 19, 2008

Interpreting the results of data warehouse proofs-of-concept (POCs)

When enterprises buy new brands of analytic DBMS, they almost always run proofs-of-concept (POCs) in the form of private benchmarks. The results are generally confidential, but that doesn’t keep a few stats from occasionally leaking out. As I noted recently, those leaks are problematic on multiple levels. For one thing, even if the results are to be taken as accurate and basically not-misleading, the way vendors describe them leaves a lot to be desired.

Here’s a concrete example to illustrate the point. One of my vendor clients sent over the stats from a recent POC, in which its data warehousing product was compared against a name-brand incumbent. 16 reports were run. The new product beat the old 16 out of 16 times. The lowest margin was a 1.8X speed-up, while the best was a whopping 335.5X.

My client helpfully took the “simple average” — i.e. the mean – of the 16 factors, and described this as an average 62X drubbing. But is that really fair? Read more

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