Sponsored by SearchStorage.com
The attributes of big data applications are often described as the four Vs: volume, velocity, variety and variability. Taken singly, any one of those traits would pose a serious challenge to traditional storage systems; when combined, they force a rethinking of the very storage architectures we rely on. Processing thousands, or millions, of small files comprising structured or unstructured data from disparate sources would strain a typical NFS/CIFS-based file storage system, but new techniques such as object storage and distributed architectures can cut the task down to size, literally breaking it into more digestible chunks that can be processed in parallel. This buyer’s checklist describes the key capabilities and features a storage system will need to handle big data analytics. The goal is, of course, for the four Vs to add up to a fifth: value. Access >>>
Table of contents
- Storage for big data applications
- Big data storage architectures
- IF-THEN decisions for big data storage
Premium Content for Free.
More Premium Content Accessible For Free
Big data storage challenges associated with rich media files
Scale-out network-attached storage (NAS) is the primary technology to handle big data needs in the media and entertainment (M&E) space. Using ...
Storage pros reap rewards in 2013 salary survey
Our Storage magazine/SearchStorage.com 2013 Salary Survey offers encouraging news: pay for storage pros rose again to an average of $98,082. ...
The benefits of data archive storage
Data archiving is firmly entrenched as a storage management best practice. SearchStorage surveys indicate that 70% of companies use some form of ...