Oracle might be displaying more interest in data analytics, but the company’s playing its proverbial cards close to the vest when it comes to revealing an overarching strategy. At this year’s OpenWorld conference in San Francisco, Oracle rolled out two new products designed to make corporate data-crunching a little more streamlined: an in-memory option for the flagship Oracle 12c database, with the ability to store data in both row and columnar format, and a monster M6-32 “Big Memory Machine” with 32TB of RAM backed by the new Parc M6 processor. It’s clear that Oracle wants to battle toe-to-toe with IBM, SAP, and other tech giants for the privilege of analyzing companies’ massive datasets. What’s less clear is how Oracle, on a tactical level, plans on actually conducting that battle. Oracle president Mark Hurd spent his OpenWorld keynote discussing Big Data (hat tip to Forbes for the blow-by-blow), but his actual talking points were strictly rote: the amount of data stored by companies is exponentially increasing, those companies need sophisticated software to make sense of it all, stagnant IT budgets are only making everything worse, and so on and so on. In order to meet that demand for mature data-crunching, Oracle plans on releasing multiple pieces of software, including updates to its Oracle Big Data Appliance that will allow clients to better utilize (and secure) Hadoop and other popular analytics frameworks; and given Oracle’s need to keep its hardware sales humming (or at least not totally stagnant), the company will continue to push its servers as the best possible devices for wrangling all that software on-premises. But here’s the issue: every other company with an interest in Big Data is doing exactly that sort of thing. SAP, IBM, Microsoft, Intel, EMC (via Pivotal and its other subsidiaries/offshoots), and roughly a billion startups are all pursuing how to adapt the ecosystem’s most popular frameworks and open-source software to their own profit-generating ends; a few with the capability are also exploring how to best combine hardware and software for superior analytics (Intel and IBM spring to mind). Every time one company plunges into a particular area—such as SAP with its HANA in-memory technology, which Oracle’s new releases are very explicitly designed to counter—the others follow it in short order. So if Oracle does have a data-analytics strategy, it probably needs to be something more than simply following what everybody else is doing, and trusting that its brand name can somehow carry it to profit and glory; the data analytics ecosystem is too crowded and fast-moving for that sort of strategy to work with any assurance. This isn’t a world for “fast followers” anymore. But it’s just as likely that Oracle is keeping the contours of its longer-term strategy hidden for the time being. Image: ollyy/Shutterstock.com Is Oracle Hiding its Data-Analytics Strategy?
Oracle might be displaying more interest in data analytics, but the company’s playing its proverbial cards close to the vest when it comes to revealing an overarching strategy. At this year’s OpenWorld conference in San Francisco, Oracle rolled out two new products designed to make corporate data-crunching a little more streamlined: an in-memory option for the flagship Oracle 12c database, with the ability to store data in both row and columnar format, and a monster M6-32 “Big Memory Machine” with 32TB of RAM backed by the new Parc M6 processor. It’s clear that Oracle wants to battle toe-to-toe with IBM, SAP, and other tech giants for the privilege of analyzing companies’ massive datasets. What’s less clear is how Oracle, on a tactical level, plans on actually conducting that battle. Oracle president Mark Hurd spent his OpenWorld keynote discussing Big Data (hat tip to Forbes for the blow-by-blow), but his actual talking points were strictly rote: the amount of data stored by companies is exponentially increasing, those companies need sophisticated software to make sense of it all, stagnant IT budgets are only making everything worse, and so on and so on. In order to meet that demand for mature data-crunching, Oracle plans on releasing multiple pieces of software, including updates to its Oracle Big Data Appliance that will allow clients to better utilize (and secure) Hadoop and other popular analytics frameworks; and given Oracle’s need to keep its hardware sales humming (or at least not totally stagnant), the company will continue to push its servers as the best possible devices for wrangling all that software on-premises. But here’s the issue: every other company with an interest in Big Data is doing exactly that sort of thing. SAP, IBM, Microsoft, Intel, EMC (via Pivotal and its other subsidiaries/offshoots), and roughly a billion startups are all pursuing how to adapt the ecosystem’s most popular frameworks and open-source software to their own profit-generating ends; a few with the capability are also exploring how to best combine hardware and software for superior analytics (Intel and IBM spring to mind). Every time one company plunges into a particular area—such as SAP with its HANA in-memory technology, which Oracle’s new releases are very explicitly designed to counter—the others follow it in short order. So if Oracle does have a data-analytics strategy, it probably needs to be something more than simply following what everybody else is doing, and trusting that its brand name can somehow carry it to profit and glory; the data analytics ecosystem is too crowded and fast-moving for that sort of strategy to work with any assurance. This isn’t a world for “fast followers” anymore. But it’s just as likely that Oracle is keeping the contours of its longer-term strategy hidden for the time being. Image: ollyy/Shutterstock.com 