Sanbolic Enhancing Melio to V5.5

Sanbolic, Inc. announced the availability of Melio Release 5.5, an enhanced version of the company's software-defined data acceleration platform.

Melio5.5 supports massive-scale distributed storage architectures and introduces new enterprise features designed to optimize and enable scale-out of solid state and flash memory usage. It also adds support for WORM devices in cross-datacenter, geo-distributed applications.

 

Using the Melio5.5 software with commodity server and storage hardware (e.g. PCIe flash, SDD, HDD), organizations can create storage systems that meet tier 1 requirements for data management, data protection, performance and scale-with economics resembling the the world's largest and most efficient cloud data centers. By implementing Sanbolic's platform and approach, enterprises can save millions of dollars in operating and capital expenses.

New Features
The economics of flash have limited its use to primarily serving as an acceleration platform for databases. New capabilities in Melio5.5 enable enterprises to reap the performance benefits of flash for a broader set of applications. The software combines world-class data and storage management capabilities across legacy storage and flash devices - at the host layer - as well as intelligent data placement. As a result, enterprises are able to balance 'price to capacity' ratios in ways that have never before been possible. By offering this approach, Melio5.5 creates a larger total available market for flash adoption.

The second patent addresses systems scale-out. Melio supports up to 2,048 nodes and 65,000 storage devices per server cluster. Its distributed lock manager technology is fully symmetrical and all machines in a cluster are lock servers to ensure that no server ever becomes a bottleneck. In the approach, locks change ownership over the network and only the previous owners of the lock can participate in communication-reducing network traffic to an absolute minimum, enabling efficient and high performing scale-out in hundreds of nodes.

Author: Anonymous

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