Search
Languages
<
2 min read

DataCore Software-Defined Storage Wins Virtualization and Cloud Review Editor’s Choice Award

The editors of Virtualization and Cloud Review have just announced DataCore’s SANsymphony™ software-defined storage solution as a recipient of its annual editor’s choice awards and this marks DataCore’s third consecutive editor’s choice award from the publication.

Industry expert Dan Kusnetsky notes that DataCore is awesome because its “software-defined storage offers a clever use of storage virtualization and network virtualization technology that supports off-the-shelf storage systems and provides outstanding performance. (Just review DataCore’s Storage Performance Council SPC-1 benchmark results and compare them to those offered by competitors.)” Kusnetsky also noted that DataCore’s intelligent use of processor and storage capacity puts it ahead of the rest.

SANsymphony software-defined storage was also recently awarded the Storage Project of the Year at the 2017 SVC Awards in honor of its five year install at Grundon Recycling, the UK’s largest recycling company, and Best Virtualization Software in Redmond Channel Partner’s editor’s choice awards: Top Products for Microsoft Partners, among other notable industry honors received.

DataCore is the company that pioneered the concept of software-defined storage — abstracting and automating the data services and management of underlying storage capacity to free customers from vendor lock-in and to deliver unrivaled performance and data protection at a fraction of the cost of comparable alternatives. DataCore software-defined storage is powered by Parallel I/O technology to maximize IT infrastructure performance, availability and utilization. It helps to provide organizations with the agility needed to meet the many challenges of transforming business in the digital age, while providing responsive, reliable and seamless access to data automatically anywhere it is needed.

Software-defined is now the vehicle to modernization and the bridge to digital transformation that unifies old and new technologies, making underlying changes invisible to the applications on which organizations depend. Unlike others offering stop-gap “rip and replace” solutions, DataCore’s approach breaks down silos and provides customers with a choice of entry points and common management services spanning the continuum of server SANs, software-defined storage, hyperconvergence and hybrid-cloud deployment models, all while preserving the value of existing investments in storage. This technology, proven in thousands of diverse real-world customer sites, makes it easy for companies to address change, manage in common a range of deployment choices and add new and future technologies such as flash, NVMe, cloud, and more – without disruption to business applications.

And that’s why editors and customers alike love DataCore software-defined storage. Users report a 75% reduction in storage costs; 10x performance increase; 100% reduction in storage-related downtime; 90% decrease in time spent on routine storage tasks; and more. Additional feedback from DataCore customers can be found by looking at our TechValidate Customer Surveys and Customer Testimonials.


Request a 30-day free trial of DataCore’s software-defined storage and see for yourself, or request a 15-minute live demo with one of our technical experts today!

Intelligent Use of Processor and Storage Capacity Puts DataCore Ahead of the Rest

Data Storage Solutions for Your Every IT Need

Talk with a solution advisor about how DataCore Software-Defined Storage can make your storage infrastructure modern, performant, and flexible.

Get Started

Related Posts
 
DataCore’s 2021 Awards Focus on Innovation & Customer
Vinod Mohan
DataCore’s 2021 Awards Focus on Innovation & Customer
 
DataCore Recognized as a Finalist in the 2019 CRN Tech Innovator Awards
DataCore Recognized as a Finalist in the 2019 CRN Tech Innovator Awards
 
Patented Approaches to Parallelism to improve I/O Performance on a Multi-Core System
Nick Connolly
Patented Approaches to Parallelism to improve I/O Performance on a Multi-Core System