Analysis of data warehouse appliance vendor DATAllegro and its products. Related subjects include:

April 5, 2008

Positioning the data warehouse appliances and specialty DBMS

There now are four hardware vendors that each offer or seem about to announce two different tiers of data warehouse appliances: Sun, HP, EMC, and Teradata. Specifically:

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January 14, 2008

Intelligent Enterprise’s list of 12/36/48 vendors

I’m getting a flood of press releases today, because many of the companies I write about were selected to Intelligent Enterprise’s list of 12 most influential vendors plus 36 more to watch in the areas Intelligent Enterprise covers (which seems to be pretty much the analytics-related parts of what I write about here and on Text Technologies). It looks like a pretty reasonable list, although I think they forced the issue in some of the small analytics vendors they selected, and of course anybody can quibble with some of the omissions.

Among the companies they cited, you can find topical categories here for IBM (and Cognos), Informatica, Microsoft, Netezza, Oracle, SAP/Business Objects (both), SAS, and Teradata; QlikTech; Cast Iron, Coral8, DATAllegro, HP, ParAccel, and StreamBase; and Software AG. On Text Technologies you’ll find categories for some of the same vendors, plus Attensity, Clarabridge, and Google. There also are categories for some of these vendors on the Monash Report.

December 14, 2007

A quick survey of data warehouse management technology

There are at least 16 different vendors offering appliances and/or software that do database management primarily for analytic purposes.* That’s a lot to keep up with,. So I’ve thrown together a little overview of the analytic data management landscape, liberally salted with links to information about specific vendors, products, or technical issues. In some ways, this is a companion piece to my prior post about data warehouse appliance myths and realities.

*And that’s just the tabular/alphanumeric guys. Add in text search and you run the total a lot higher.

Numerous data warehouse specialists offer traditional row-based relational DBMS architectures, but optimize them for analytic workloads. These include Teradata, Netezza, DATAllegro, Greenplum, Dataupia, and SAS. All of those except SAS are wholly or primarily vendors of MPP/shared-nothing data warehouse appliances. EDIT: See the comment thread for a correction re Kognitio.

Numerous data warehouse specialists offer column-based relational DBMS architectures. These include Sybase (with the Sybase IQ product, originally from Expressway), Vertica, ParAccel, Infobright, Kognitio (formerly White Cross), and Sand. Read more

November 7, 2007

Vertica update – HP appliance deal, customer information, and more

Vertica quietly announced an appliance bundling deal with HP and Red Hat today. That got me quickly onto the phone with Vertica’s Andy Ellicott, to discuss a few different subjects. Most interesting was the part about Vertica’s customer base, highlights of which included:

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October 25, 2007

DATAllegro discloses a few numbers

Privately held DATAllegro just announced a few tidbits about financial results and suchlike for the fiscal year ended June, 2007. I sent over a few clarifying questions yesterday. Responses included:

All told, it sounds as if DATAllegro is more than 1/3 the size of Netezza, although given its higher system size and price points I’d guess it has well under 1/3 as many customers.

Here’s a link. I’ll likely edit that to something more permament-seeming later, and generally spruce this up when I’m not so rushed.

October 19, 2007

Gartner 2007 Magic Quadrant for Data Warehouse Database Management Systems

February, 2011 edit: I’ve now commented on Gartner’s 2010 Data Warehouse Database Management System Magic Quadrant as well.

It’s early autumn, the leaves are turning in New England, and Gartner has issued another Magic Quadrant for data warehouse DBMS(Edit: As of January, 2009, that link is dead but this one works.) The big winners vs. last year are Greenplum and, secondarily, Sybase. Teradata continues to lead. Oracle has also leapfrogged IBM, and there are various other minor adjustments as well, among repeat mentionees Netezza, DATAllegro, Sand, Kognitio, and MySQL. HP isn’t on the radar yet; ditto Vertica. Read more

October 12, 2007

Three ways Oracle or Microsoft could go MPP

I’ve been arguing for a while that Oracle and Microsoft are screwed in high-end data warehousing. The reason is that they’re stuck with SMP (Symmetric Multi-Processing) architectures, while Teradata, Netezza, DATAllegro, and many others enjoy the benefits of MPP (Massively Parallel Processing). Thus, Teradata and DATAllegro boast installations in the hundreds of terabytes each, while Oracle and Microsoft users usually have to perform unnatural acts of hard-coded partitioning even to reach the 10 terabyte level.

That said, there are at least three ways Oracle and/or Microsoft could get out of this technical box:

1. They could buy or just partner with MPP vendors such as Dataupia, who offer plug-compatibility with their respective main DBMS.

2. They could buy whoever they want, plug-compatibility be damned. Presumably, they’d quickly add a light-weight data federation front-end to give the appearance of integration, then merge the products more closely over time.

3. They could develop or buy technology like DATAllegro’s, which essentially federates instances of an ordinary SMP DBMS across nodes of an MPP grid (Greenplum does something similar). I imagine that, for example, ripping Ingres out of DATAllegro and slotting in Oracle instead would be a pretty straightforward exercise; even without dramatic change to any of the optimizations, the resulting port would be something that ran pretty quickly on Day 1.

Bottom line: Oracle and Microsoft are hemorrhaging at the data warehouse high end now. But there are ways they could stanch the bleeding.

October 8, 2007

Hot buzzword — multidimensional partitioning

Teradata finally announced multidimensional range partitioning in Version 12, not that they kept their plans in that regard a big secret. DATAllegro has also shipped multidimensional partitioning to at least one customer. Other vendors — well, I’ll stop there, given my ongoing atttitude problems about vendors’ self-defeating NDAs.

Whether or not multidimensional partitioning is a big improvement over single-dimensional will of course depend a great deal on the details of a particular database. Teradata used a figure of 30% performance improvement, but that’s surely just an example. Certainly in some extreme cases one could have a rather large reduction in the amount of data retrieved, and correspondingly a many-times-X improvement in the performance of certain important queries. Read more

September 28, 2007

Oracle sincerely flatters DATAllegro

Actually, I’m kidding with the post title; I doubt that Oracle’s new deal with DATAllegro partners Dell and EMC has much to do with DATAllegro at all. Rather, I think it’s an example of a trend I’m also sensing* from other major hardware vendors — doing deals with multiple data warehouse software suppliers to cover different hardware size ranges. This just happens to be the first one to be announced.

*How’s that for a nice, vague euphemism?

DATAllegro is targeted at warehouses sized, at a minimum, in the tens of terabytes of user data. Oracle’s technology works well enough up into at least the multi-terabyte range — unless you’re looking to get the best possible price and/or performance on your system — but then things start getting dicey. So there isn’t a lot of overlap between the two Dell/EMC offerings. Read more

September 27, 2007

Four anonymous Netezza fans

I just found a blog post asking about Netezza that elicited quite a few responses, including at least four that purported to be from people whose companies had selected Netezza in a POC (Proof Of Concept) bake-off. One says Netezza was super-fast, even over DATAllegro, and DATAllegro’s professional services were lacking. One says Netezza is 50X faster than traditional alternatives on some queries, but up to 2X slower on some others. Two others just expressed love (or at least commitment) without giving details.

I haven’t yet looked through the rest of the responses in the thread.

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