http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/ Choices in data management and analysis Fri, 08 Aug 2008 00:29:50 +0000 http://wordpress.org/?v=2.5.1 http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-19689 DBMS2 — DataBase Management System Services»Blog Archive » Opportunities for disruption in the OLTP database management market (deck-clearing post #2) Tue, 27 Feb 2007 11:13:52 +0000 http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-19689 [...] · 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. • • • [...] [...] · 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. • • • [...]

]]> http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-12836 Text Technologies»Blog Archive » Enterprise-specific web search: High-end web search/mining appliances? Mon, 23 Oct 2006 00:28:05 +0000 http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-12836 [...] 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.) [...] [...] 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.) [...]

]]> http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-9737 DBMS2 — DataBase Management System Services»Blog Archive » Introduction to Kognitio WX-2 Thu, 05 Oct 2006 12:56:49 +0000 http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-9737 [...] Their core technology is MPP/shared-nothing data warehousing. [...] [...] Their core technology is MPP/shared-nothing data warehousing. [...]

]]> http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-9551 DBMS2 — DataBase Management System Services»Blog Archive » Data mining is driving much of data warehousing Wed, 04 Oct 2006 10:18:13 +0000 http://www.dbms2.com/2006/10/03/vendor-segmentation-for-data-warehouse-dbms/#comment-9551 [...] 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.) [...] [...] 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.) [...]

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