Tuesday, April 22, 2014

Virtualization Impact on Big Data

To make a big impact using Big Data, a company CIO needs to use cheap storage options which can scale in and scale out to satisfy the variety needs of big data.

Virtualization
 provides exactly the same option. Virtualization can further be divided into following categories:
  • Hardware Virtualization
  • Application Virtualization
  • Network Virtualization
  • Process and Memory Virtualization 
Each of these virtualization can have significant impact on Big Data platofrms. Some of the Virtualization benefits can be summed as:
  • Virtualization helps to ensure that big data platform can scale as needed to handle the large volumes and varied types of data included in data analysis.
  • An enterprise might not have the finances to procure the array of inexpensive machines for its first pilot. Virtualization enables companies to tackle larger problems that have not yet been scoped without a huge upfront investment.
  • Big data computing algorithms like Map reduce works well in a virtualized environment with respect to storage and computing. Amazon EMR encapsulates the MapReduce engine in a virtual container so that you can split your tasks across a host of virtual machine (VM) instances. Hence it provides better performance.
  • Virtualizing the network helps in improving the capability to manage the large distributed data required for big data analysis.


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