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New storage architectures slowly making inroads
This article is part of the February 2014 Vol. 12 No. 12 issue of Storage magazine
Over the last few years alternatives to traditional storage architectures have emerged that may prove transformative. Learn which ones our readers are using in their storage shops. Storage advances slowly, but it doesn't stand still. Recently, alternatives to traditional storage architectures have emerged that may prove transformative. Some are evolutionary (scale-out NAS, converged infrastructures), while others are downright revolutionary (object storage, software-defined storage). Most of our survey respondents still rely on good old DAS (62%), SAN (59%) and NAS (59%) to handle their average data capacity of 372 TB, but newer techs are beginning to share the load: 23% have deployed clustered NAS and 14% are evaluating it. Similarly, cloud-integrated storage and object storage are past the curiosity phase and are in actual use by 18% and 16%, respectively. Clustered NAS adopters take "scale-out" seriously, with a whopping average capacity of 327 TB. Archive (25%) and cloud (25%) are the classic use cases for object, but 33% ...
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Features in this issue
This "Sweet 16" roster of storage products represents the leading technical innovation of the past year.
Don't make your DR planning process harder than it is by trying to do too much or cutting corners. Careful planning is key to a successful recovery.
There are two sides to the big data story: analytics using vast numbers of small files, and dealing with storage for really big files.
Our latest survey charts the storage architecture alternatives readers are using in their storage shops.
Columns in this issue
Cloud closures, flash-in-the-pan solid-state vendors … storage might seem a little more dangerous these days, but it just might be innovation at work.
Filling drives with helium doesn't advance the art of hard disk design, it just makes it possible to stuff more old tech into a new package.
There aren't many reasons not to virtualize your servers, but there are plenty of compelling data protection reasons to virtualize them all.
Using Hadoop to drive big data analytics doesn't necessarily mean building clusters of distributed storage; a good old array might be a better choice.