Major players in Software Defined Storage (SDS) Market are EMC, Hitachi Data Systems, IBM, Vmware, NetApp, Nexenta and many others.
(PRWEB) December 11, 2014
The research report on Software Defined Storage (SDS) Market defines the global market to provide an in-depth analysis of the growth opportunities, current trends and revenue forecasts. According to the report, the market is estimated to grow at a CAGR of 34.6% from 2014 to reach $6,217.6 million in 2019. As of 2014, it estimates the market to be worth $1,409.7 million.
Browse through “Software Defined Storage (SDS) Market” data with help of detailed tables, figures and ToC spread across 126 pages
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The usage of storage virtualization or internal data center depends on the variables like budget, mission, values and preferences. The expenses of setting up and maintaining the data center space along with the perfect environmental, security and performance conditions are high. Limited financial resources create trouble for many small to medium-sized companies looking to manage data center space. As a result, these companies are moving towards employing SDS solutions that help optimizing their operational costs. These solutions help in federating and virtualizing storage units for the advantage of its users. SDN solutions automatically allocate the storage units dynamically on the data centers based on public and private infrastructures.
The report broadly segments the Software Defined Storage Market on the basis of the types of components, organization size, business verticals, and geographic regions. Analysis of all these segments provides details about the growth factors, restraints, challenges and competitive landscape for the market.
According to the report, financial services, healthcare, and manufacturing verticals will be the largest adopters of storage virtualization software. Based on geographic regions, the report expects North America to be the largest market in terms of revenue contribution, while predicts Asia Pacific (APAC) to show higher growth rate during the forecasting period.
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