In this session I described and compared the four distinct data retrieval technologies available from IBM.

Choices are good to have, but how do you choose which technology to apply to a particular business use case? Learn how these techniques differ, including their relative strengths and weaknesses.
– The traditional RDBMS, relying primarily on indexes to speed access
– The new BLU Acceleration columnar compression and memory-optimized database
– IBM PureData System for Analytics (Netezza), which deploys racks of Field Programmable Gate Array (FPGA) processors to parse data
– IBM InfoSphere BigInsights,  the IBM distribution of Hadoop

Click here for the recording of the webinar.  The presentation materials: IBM Data Retrieval Technologies RDBMS BLU Netezza and Hadoop

The trip to Prague, CZ last week for the International DB2 Users Group meeting was fabulous.  The city certainly has changed since I’ve been there – all for the better.  It seems more cosmopolitan, the people seem younger, more vibrant than I remember from 2004.  And the dining and music – Kim and I attended jazz and classical music concerts and enjoyed Madame Butterfly at the Prague State Opera – were amazing CutterWelderMaestro.

Here’s my pitch on “IBM Data Retrieval Technologies” if you weren’t able to attend.  IDUG EMEA 2014 E7 – IBM Data Retrieval Technologies – RDBMS BLU IBM Netezza and Hadoop

Next year IDUG EMEA will be in Dublin.  Hope you can join us for a Guinness by the River Liffey.

From November 9 – 14 I will be visiting one of the most charming cities on the planet when I attend the International DB2 Users Group (IDUG) conference in Prague, CZ.  I will present “IBM Data Retrieval Technologies : RDBMS, BLU, IBM Netezza and Hadoop”.  It will be session E7 on Tuesday, November 11 from 3:15 to 4:15 p.m.  Please consider attending IDUG Europe and joining me at this session.

Abstract:  IBM offers four distinct data retrieval technologies: the traditional RDBMS, which primarily relies on indexes to speed access; the new BLU Acceleration columnar compression database; IBM PureData System for Analytics (IBM Netezza), which deploys racks of Field Programmable Gate Array (FPGA) processors to parse the data; and IBM InfoSphere BigInsights, which is the IBM distribution of Hadoop. Choices are good to have, but how do you choose which technology to apply to a particular business use case? In this session, you learn how these techniques differ, including their relative strengths and weaknesses, to help you make an informed choice.

I had the opportunity to chat with Jeff Kelly, Big Data Analyst, at Wikibon.  You can about our discussion on the Silicon Angle blog or view the interview here.