My Economics teacher once told me that if I wanted a job for life, then I should be an undertaker. Demand is always assured, he said. If there were a single database guru out there to deliver the same sagacious type of advice, he or she would surely say, “Sell your database to government, the financial market and defence.” Demand is again assured.
That’s how Sybase makes its money right now, it surely constitutes a good dollop of what fills Oracle’s coffers these days and it is much of what makes the commercially supported open source RDBMS Ingres what it is today. So how do these companies keep the governments and enterprise-scale organisations of this world satiated in terms of the tabular treats that they must roll out to keep them buying?
Ingres for one has just announced a project with VectorWise, a spin off from the database research team at Centrum Wiskunde & Informatica of Amsterdam, a research institute in mathematics and computer science. With backing from Intel, Ingres and VectorWise are attempting to build a database engine that derives an increased quotient of its power from modern hardware processor and storage performance.
Developers and DBAs in this space will no doubt be attracted by the promise of being able to perform new data analysis tasks that were previously not feasible. Ingres is using CEO Roger Burkhardt’s name to put out this upbeat quip, “This ability to extract deep insights from detailed business data at the ‘speed of thought’ will empower all leaders to make better business decisions.”
Ingres says that business and infrastructure software has failed to keep up with the continuous advancements in chip and memory technologies. This comment of course being highly redolent of news I commented on earlier this month from Sybase relating to the company’s IQ 15.1 column-based analytics server, which ships with ‘in-database’ analytics functionality. Although of course, Ingres argues that it is the, “combination of open source software and a less costly hardware server,” that makes the real difference when it comes to in-data analytics processing.
Massive But Agile: Best Practices For Scaling The Next-Generation Enterprise Data Warehouse – this is a paper by senior analyst James Kobielus of Forrester Research and it sums up the subject matter of this blog extremely accurately.