October 3, 2006

Vendor segmentation for data warehouse DBMS

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

Several vendors are offering links to Gartner’s new Magic Quadrant report on data warehouse DBMS. (Edit: This is now a much better link to the 2006 MQ.) Somewhat atypically for Gartner, there’s a strict hierarchy among most of the vendors, with Teradata > IBM > Oracle > Microsoft > Sybase > Kognitio > MySQL > Sand, in each case on both axes of the matrix. The only two exceptions are Netezza and DATallegro, which are depicted as outvisioning Microsoft somewhat even as they trail both Microsoft and Sybase in execution.

Gartner Magic Quadrants tend to annoy me, and I’m not going to critique the rankings in detail. But I do think this particular MQ is helpful in framing a vendor segmentation, namely:

  1. Big full-spectrum MPP/shared-nothing vendors: Teradata and IBM.
  2. MPP/shared-nothing appliance upstarts: Netezza and DATallegro
  3. Big SMP/shared-everything vendors who also are apt to be your OLTP incumbent, and who want to integrate your software stack soup-to-nuts: Oracle and Microsoft
  4. Niche vendors: Pretty much everybody else

As I see it, the first battle is Groups 1&2 vs. Group 3, and Groups 1&2 are winning. All is not lost for Group 3, however, because it makes a certain sense to have an OLTP-like enterprise warehouse that offloads the more analytical warehousing to specialists from Groups 2, 4, or even 1. Or, if your warehousing needs are lightweight enough, just use your favorite OLTP DBMS vendor for everything and don’t worry about it.

The next question is Group 2 vs. Group 1. That one will be interesting. Certainly there are workloads the Group 2 guys will have trouble handling unless they narrow their technical difference vs. the Group 1 guys. On the other hand, for the workloads the Group 2 guys are currently tuned for, it will be a strain for the Group 1 guys to be fully price-competitive, notwithstanding their claims of “Oh, we can do everything those little guys can if we just turn off enough of our features.” And what happens if Oracle or Microsoft decides to simply buy DATallegro or Netezza? And for that matter, what happens if IBM actually gains more traction for OLTP uses for distributed DB2, and/or for its XML engine?

This is going to be a fascinating market to watch.

Comments

5 Responses to “Vendor segmentation for data warehouse DBMS”

  1. DBMS2 — DataBase Management System Services»Blog Archive » Data mining is driving much of data warehousing on October 4th, 2006 6:18 am

    [...] That was just the analysis. There’s also data mining scoring. In data mining scoring you substitute numbers for values in a table, and then do a row-by-row weighted sum of what results. Or else you do this real-time, for single rows, if that’s your preferred way of deploying things. Just about everybody agrees this is better done “in the DBMS” than in an extract file. Indeed, since the batch version of this is table-scan-to-the-max, scoring turns out to be ideally suited for data warehouse appliances and other MPP/shared-nothing products. (That doesn’t – and shouldn’t – stop Oracle from making scoring integration part of its data mining value-added pitch.) [...]

  2. DBMS2 — DataBase Management System Services»Blog Archive » Introduction to Kognitio WX-2 on October 5th, 2006 8:56 am

    [...] Their core technology is MPP/shared-nothing data warehousing. [...]

  3. Text Technologies»Blog Archive » Enterprise-specific web search: High-end web search/mining appliances? on October 22nd, 2006 8:28 pm

    [...] 1. There’s a clear technology trend at the high-end of the relational data warehousing world: Massively multi-parallel “shared-nothing” systems are winning over the symmetric multi-processing “shared-everything” systems that dominate the OLTP RDBMS world. (I’ve written about that at length over on DBMS2, e.g. in this post.) [...]

  4. DBMS2 — DataBase Management System Services»Blog Archive » Opportunities for disruption in the OLTP database management market (deck-clearing post #2) on February 27th, 2007 7:13 am

    [...] · The existing order in analytic DBMS is under fierce attack. It’s becoming ever more widely accepted that Oracle and Microsoft don’t have the best products for data warehouses. Eventually, this could undermine their mystique in the OLTP space as well. • • • [...]

  5. Gartner’s 2008 data warehouse database management system Magic Quadrant is out | DBMS2 -- DataBase Management System Services on January 21st, 2009 9:48 pm

    [...] links to the 2008 Gartner Data Warehouse Database Management System MQ.  My posts on the 2007 and 2006 MQs have also been updated with working [...]

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