Main image of article HP’s The Machine Could Crush Big Data Problems
Big Data is only getting bigger: Over the next several years, it’s probable—if not outright inevitable—that businesses will find themselves faced with the need to crunch billions (maybe even trillions) of records, analyze increasingly massive datasets (often in a matter of seconds or minutes) and transmit that data around the world. Tech firms are already working on solutions to address Bigger Data: SAP, IBM and Oracle, for example, have all announced in-memory technology designed to greatly speed up analytics. The open-source community continues to refine Apache Hadoop. In the wake of last summer’s NSA revelations, tech firms have also devoted considerable resources to figuring out how to better encrypt clients’ data both in motion and at rest. Click here for analytics jobs. Now Hewlett-Packard’s throwing its proverbial hat into the ring with a platform it calls, rather ominously, The Machine. Combining memristors (ultra-fast, nano-scale components capable of both storage and processing) with custom chips and fiber-optic transistors, The Machine—at least in theory—could process hundreds of petabytes in nanoseconds, all while displaying enviable energy efficiency. On paper, the technology behind The Machine can fit into all sorts of form-factors, from hardcore data-center servers to ultra-light laptops. (“Why do we call it The Machine? When we first started developing it, we wanted to be very careful not to call it a server, workstation, PC, device or phone, because it actually encompasses all of those things,” reads a note on HP’s Next website. “So as we were waiting for Marketing to come up with a cool code name for the project, we started calling it The Machine—and the name stuck.”) In order to ensure The Machine runs effectively across multiple types of hardware, HP has teams hard at work on different Machine-specific operating systems, including one for Google Android. HP, which thinks it can release the first examples of The Machine in either 2017 or 2018, boasts that the technology will help companies with secure storage, data aggregation and analytics (including reactive insight to real-time events). Even if the platform lives up to the hype, though, HP likely won’t have long to exploit it before its rivals produce something similar: If data analytics is an arms race, it remains a fierce one for the foreseeable future.

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Image: HP