Compuverde Unveils Game-Changing Big Data Virtualization and Storage Suite

Gateway and Object Store Solutions Deliver Efficiency, Cost-Effectiveness to Service Providers, Telcos and Large Enterprises

News provided by

Compuverde

Aug 20, 2012, 08:00 ET

KARLSKRONA, Sweden, Aug. 20, 2012 /PRNewswire/ -- Compuverde, the Big Data virtualization and storage solution for service providers, telecommunications companies and enterprises, today announced the launch of its combined product suite for efficient, cost-effective Big Data virtualization and storage. The new Gateway and Object Store offerings are aimed at increasing ROI for large enterprises by reducing energy usage costs by up to 50 percent.

With data storage demands rising exponentially each year, service providers, telcos and large enterprises are searching for ways to leverage customer data efficiently and safely while controlling spiraling energy expenses.  By shrinking energy costs up to 50 percent, Compuverde's new software suite enables these organizations to leverage their huge customer base more efficiently, extracting a massive competitive advantage in storage economies of scale.

When used together, Compuverde's product suite lowers Big Data hardware needs and capital expenditure. Compuverde helps keep costs down by working with less expensive, low-performing storage units, forming them into a high-performance storage cloud. The use of a symmetric architecture eliminates bottlenecks that are a costly part of traditional storage solutions. With no single points of failure or performance bottlenecks to protect, customers are free to choose less expensive off-the-shelf hardware.

Key Facts:

  • Increased performance and reliability: Data is stored in multiple copies and can be separated geographically among different locations within the cluster.  A highly efficient fault recovery process allows for nearly complete redundancy.
  • Self-healing clusters: When a disk or storage node breaks down, the cluster self-heals by recreating the missing data from the damaged node in the cluster, resulting in a temporary capacity decrease.
  • Simplified scalable deployment and maintenance: The Compuverde suite avoids the need for special purpose or central nodes, greatly simplifying deployment and maintenance.
  • Lower costs: By leveraging clusters of standardized servers, Compuverde stores petabytes of accessible data at the lowest possible cost.

Supporting Quotes:

Stefan Bernbo, CEO, Compuverde, said: "With Compuverde, the cache is synchronized at all times with the storage nodes, resulting in high performance and reliability. A highly efficient fault recovery process allows for nearly complete redundancy. Our new Gateway and Object Store suite increases performance up to 400 percent in unstructured and structured Big Data storage compared to existing products in the market." 

Eric Slack, senior analyst, Storage Switzerland, said: "Storage is an Achilles' heel for Big Data virtualization.  Running thousands of virtual machines can lead to significant data usage costs prompting large enterprises to explore ways of reducing expenditures on infrastructure and operations.  Being able to use commodity hardware while reducing energy consumption in their data centers could provide a competitive edge to service providers and telcos looking to compete in the hosted cloud sphere."

Supporting Resources:

Social Media Destinations:

LinkedIn: www.linkedin.com/company/compuverde 
YouTube: www.youtube.com/user/compuverde

About Compuverde

Compuverde is the leader in Big Data virtualization and storage solutions for service providers, telecommunications companies and enterprises. Compuverde's solution combines telco-grade "five nines" reliability and highly-scalable cloud-based object storage with integrated cache functionality, delivering 50 percent lower energy usage and enabling the use of environmentally-friendly hardware. For more information, visit www.compuverde.com.

Editorial Contact:

Peggy Tierney
Nadel Phelan, Inc.
(831) 440-2405
[email protected]

SOURCE Compuverde

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