Storage Virtualization Software
Essential To Your Microsoft®
Virtualization Strategy

Experience SANs with the highest availability, fastest performance and fullest utilization

Virtually everything hinges on storage. Server and desktop consolidation, in particular, place extraordinary demands on it. Too often, disks slow down, interrupt or endanger these centralized IT operations not because they are poorly designed or built, but because they are physically constrained. Microsoft Windows Server® 2008 Hyper-V® and Hyper-V Server help you to overcome similar limitations in CPU and memory, however, when it comes to advanced functions such as workload migration, load balancing, fail-over and disaster recovery, server virtualization is completely dependent on highly available (HA) shared storage. You will be shocked at the high hardware costs and major overhaul generally proposed to put such a storage infrastructure in place.

DataCore™ storage virtualization software delivers a radically simple, high availability solution to meet Hyper-V's shared storage requirements. The software abstracts your storage into idealized, virtual disks akin to virtual machines. It pools and mirrors disk blocks across available devices, despite differences in make and model. In the process, it speeds up I/O response and throughput using extensive SAN-wide caching. This lets you take optimum advantage of Microsoft's full suite of capabilities without hesitation. From a central console, you can non-disruptively provision, share, clone, replicate and expand virtual disks among physical servers and VMs. DataCore yields the highest availability, fastest performance and fullest utilization from your storage assets, making it an essential element of your Microsoft "Data Center to Desktop" Virtualization Strategy.

Total Wine & More Read Case Study [PDF]
Total Wine & More is the largest privately-owned fine wine retailer in the United States, with 62 stores in 11 states. DataCore provided Total Wine a way to grow in terms of the size of the user community it supported but also in terms of performance, simultaneously.