Big data results in big storage and big business opportunities in all storage applications.
Some galleries sell out their booths several times over, restocking from the big storage room in the back.
One of them is penetration of the enterprise market with solid state drives, an area hotly contested now by big storage and computing players like EMC, Dell and IBM.
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All the big storage companies are developing products to play in the big data space because of the storage capacity growth as well as the growth in support services for big data.
As I pointed out in Curing the Big Data Storage Fetish, much of the money currently going into big data is paying for storage.
FORBES: Ten Properties of the Perfect Big Data Storage Architecture
As a result of this flexibility and additional capabilities direct attached storage (DAS) used to build big enterprise storage systems that serve applications from big science to cloud computing will be able to offer faster performance and data protection and allowing faster data processing and content generation.
My first stop in finding patterns relevant to the perfect big data storage architecture was Quantum Corp.
FORBES: Ten Properties of the Perfect Big Data Storage Architecture
In essence, the big data storage fetish is a form of denial.
The bank turned to RainStor, which can compress data by up to 97 percent, providing big savings on storage.
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By adding more of the Brazilian varieties to the mix at certain times, Tropicana can produce not-from-concentrate OJ year-round without running up big cold-storage costs.
All in all, the company does a great job of sharing its knowledge in a way that sets them apart from the other big-name storage companies.
The announcement today that IBM is acquiring high end enterprise SSD supplier, Texas Memory makes Big Blue the latest storage company to acquire a solid state storage supplier.
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This transaction allows us to increase our focus on these technologies and to further expand on our commitment to drive growth from our core supercomputing business and our new initiatives in mid-range supercomputing, storage and big data.
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My specialties include storage technologies applied to Big Data analytics (primary), data management, virtualization, and analysis of storage infrastructure acquisition alternatives.
Quantum introduced its Lattus family of wide-area storage solutions for big data.
But Dietzen believes that Pure Storage has two big advantages over EMC.
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Virtualization plays a big role in making cloud storage possible.
Whether it is storage systems architectures or storage devices enabling big data applications the growth of content is increasing the amount of large data sets that enterprises must work with.
Next to them is a big fat bin labelled "energy storage", and it's virtually empty.
Last night's Cumbria nuclear waste storage programme provoked a big response so here are some thoughts on your feedback.
The issue of energy storage has been a big problem that, so far, has eluded solution, I commented in this column.
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Pure Storage is going after big markets.
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Other factors that will increase storage capacity growth are the creation and sharing of user generated content and the growth of machine to machine communication (and thus information storage) such as smart grid networks, video surveillance, big science in astronomy and physics and other emerging automated users of storage capacity.
Too many organizations think they can manage Big Data by throwing increasing amounts of storage at the problem.
Many companies incorporate LSI storage solutions to accelerate their big data applications.
The deal, expected to be finalized late this year, would allow EMC to provide complete storage infrastructure for so-called big data.
The Big Data servers can fit two petabytes of storage capacity per rack.
The product includes new levels of security, data protection, interoperability and system performance to extend EMC Isilon storage to a broader range of big data applications.
First, Web innovators, such as Facebook, Google and Yahoo, have developed a massively scalable storage and compute architecture to manage Big Data: Hadoop, which parallelizes large data sets across low-cost commodity hardware for easy scale and dramatically reducing the cost of petabyte environments.
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