IDUG Europe 2013 – More Details on the 3 Topics on Everyone’s Mind

The IDUG European conference celebrated 30 years for DB2 z/OS, 25 years of IDUG conferences, and 20 years of DB2 LUW.  With colleagues from around the world the IDUG conference helped everyone share their knowledge: company data management issues, problem situations; and understand what has been successful and what has failed.  As I wrote last week, separating the hype from the truth is one of the most important parts of IDUG because it is the only true pure DB2 user group.  The following three topics became a little clearer through the presentations, sessions, and conversations.

Big Data – Successes and failures are already happening with Big Data systems.  The successes are happening with both DB2 for z/OS, DB2 LUW with DPF and with DB2 BLU.  The failures are mainly happening with the NoSQL database crowd: Hadoop, MongoDB, Postgres and Pivotal (formerly GreenPlum) and others.
While parallel DB2 and NoSQL projects happen at companies, DB2 shows that it can handle everyone’s Big Data while the NoSQL implementation struggles or completely fails.  The NoSQL database failures are caused by programmability issues, integration issues, and indexing difficulties that I have talked about in my previous blog here at the bottom.  DB2 continues to work and can handles 100s of billions of rows in its tables and databases because of partitioning, multiple DPF nodes. It has enough capacity through data sharing and DPF or PureScale systems to scale Big Data applications linearly.

It will be interesting to note how long these NoSQL failures or struggles will keep going for these open source projects.  Discussions revealed that business units are picking and running these NoSQL databases efforts, taking budget away from traditional IT.  Time will tell how long this trend will last.

DB2 11 for z/OS – When I was on the DB2 for z/OS Experts panel one of the questions was “Which of the features of DB2 11 did we like the best?”  While I picked the new large 2GB memory frames that can be set for pinning larges buffer pools, others chose the break-in on threads capability, improved de-compression algorithm, and the INSERT improvements.  The most interesting comment I heard was that the code stability and expansion of the RBA/LRSN are the most important features.

Remember to get the DB2 z/OS white paper IDUG put together. If you are an IDUG community website member, you can find and can download it here.  Also, be on the lookout at the RedBooks website for two new IBM DB2 11 Redbooks “DB2 11 for z/OS Technical Overview” and “DB2 11 for z/OS Performance Topics.”

DB2 LUW BLU – The new DB2 version 10.5 with BLU acceleration continues to impress people with its speed and ease of use.  The DB2 LUW Tools team is looking for suggestions on which DB2 LUW monitoring tools they should enhance next:  Event Monitors, Monitor Views, ADMIN views, db2pd, db2top, MON_REPORTs, Auditing or WLM defaults?   The discussions seemed to favor db2top and Event Monitors.  Make your wishes known by contacting your IBM representative.

I will also be presenting at the Information on Demand (IOD) conference in Las Vegas November 3-7, 2013.  I will be presenting “Big Data Disaster Recovery Performance” Wednesday November 6, at 3 pm in the Mandalay Bay North Convention Center – Banyan D.

This presentation will detail the latest techniques and design architectures to provide the best Big Data disaster recovery performance.  The various hardware and software techniques will be discussed highlighting the Flash Copy and replication procedures critical to Big Data systems these days.


Dave Beulke is a system strategist, application architect, and performance expert specializing in Big Data, data warehouses, and high performance internet business solutions.  He is an IBM Gold Consultant, Information Champion, President of DAMA-NCR, former President of International DB2 User Group, and frequent speaker at national and international conferences.  His architectures, designs, and performance tuning techniques help organization better leverage their information assets, saving millions in processing costs.

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