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Q&A: Netezza to focus on workload optimized systems, CEO says

Jaikumar Vijayan | Feb. 14, 2011
One-size-fits-all model doesn't work in data warehouse market, Jim Baum says

What's driving demand for your kind of products? I think there are very real and undeniable trends on a couple of fronts here. Businesses have recognized the ability and the need to be able to extract usable business decision-making information from the data that defines their business and the ecosystem in which it operates. If you look at just about any company in the world today, they are producing extraordinary volumes of data. They are producing data in their supplier systems, in their customer systems, in their customer relationship management systems, in their ERP systems. [Companies are] going beyond traditional BI into what I would call business analytics and business optimization. Customers are now looking at the data and they are seeing that they actually are able to make predictions based on that data. Trend No. 2 is the amount of data we have to deal with here. It wasn't long ago that we all thought that a terabyte of data was a lot. Now we are starting to talk in terms of hundreds of terabytes and petabytes and soon we will be talking in terms of exabytes. Our whole idea of it is if we can make the data more manageable, then we can make it more accessible to a broader group of end users.

How do you see these trends affecting Netezza's product strategy over the next few years? In the Netezza world, you will see products that are purpose-built to support a task of archival of very large volumes of data. It is one of the things that I think makes us fit with IBM extremely well. This idea of workload-optimized environments. If you look at one of the latest workload-optimized computers that IBM is talking about, it's the Watson computer. That's a system that's purpose-built to play Jeopardy. It is, frankly, a breakthrough in natural language processing and text analytics in being able to provide responses to these Jeopardy questions in under three seconds. It is a very good example of a workload-optimized system. So that's the theme here.

Do emerging BI applications even need a data warehouse anymore? Yes absolutely. I think one of the things you hear a lot about in the market right now, especially on this topic, comes from Oracle. They are out there positioning Exadata as all things to all people. It will do OLTP [Online Transaction Processing], it will do ODS, it will do data warehousing, it will fold your shirts. It's a very interesting positioning of theirs. Because what we found at Netezza and certainly what IBM has found over many decades is there really is no one size fits all here. This idea of a workload optimized system for the task at hand is really quite important. I think when you take a product like Exadata and you say to the market that it does it all, what have you done? What you have really done is create a system that is a very complex integration of hardware and software that is designed to meet the needs of everyone and therefore probably doesn't fully meet the needs of anyone. We still see a very clear need for this idea of purpose-built workload optimized solutions like Netezza for warehousing, like Watson for winning Jeopardy games and like other solutions that IBM has for OLTP, transaction processing and other workloads.

 

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