No Screenshots 
Download Document Category: Whitepaper
Subject: Data Analytics
Vendor:
Keywords: Big Data, Big Data Analytics, NAS, SAN, SSD
Document Price: Free
Document Date: 2011-06
Document Number:
Author(s): John Webster
# of Pages: 8
Short Description:
The practitioners of Big Data Analytics processes are generally hostile to shared storage. They prefer direct-attached storage (DAS) in its various forms from solid state disk (SSD) to high capacity SATA disk buried inside parallel processing nodes. The perception of shared storage architectures—SAN and NAS—is that they are relatively slow, complex, and above all, expensive.
Full Summary:
The practitioners of Big Data Analytics processes are generally hostile to shared storage. They prefer direct-attached storage (DAS) in its various forms from solid state disk (SSD) to high capacity SATA disk buried inside parallel processing nodes. The perception of shared storage architectures—SAN and NAS—is that they are relatively slow, complex, and above all, expensive. These qualities are not consistent with Big Data Analytics systems that thrive on system performance, commodity infrastructure, and low cost.
Please download to read the rest.
Warning: Invalid argument supplied for foreach() in /var/www/wp-content/themes/evaluator/library/extensions/content-extensions.php on line 911
Big Data Analytics – Can SAN/NAS Meet the Demand?
The practitioners of Big Data Analytics processes are generally hostile to shared storage. They prefer direct-attached storage (DAS) in its various forms from solid state disk (SSD) to high capacity SATA disk buried inside parallel processing nodes. The perception of shared storage architectures—SAN and NAS—is that they are relatively slow, complex, and above all, expensive. These qualities are not consistent with Big Data Analytics systems that thrive on system performance, commodity infrastructure, and low cost.
Please download to read the rest.