Semiconductor technology is constantly evolving, basically following Moore’s law, so microcircuitry goes denser and more efficient all the time. As a result, the average installed RAM size has increased thousandfold over less than ten years and it’s not planning to stop. At the moment, it’s quite affordable to have RAM of the same capacity as some five-year-old HDD, so that opens room for some new scenarios.
It’s a common thing to require storage of extremely high performance, during mostly test and development, troubleshooting process or some niched deployments like online payment services or onthe-fly encryption. In these cases, size and data volatility are factors of lower importance, because the used data is usually temporary. Traditional solutions, like the superfast PCIe memory and newly-developed NVMe flash, are expensive and not always available when needed “right now”. Besides, for test and development, it’s most definitely overkill to utilize such advanced and costly measures.
StarWind RAM Disk takes a part of the RAM and creates a virtual storage device usable as a disk of tremendous performance. The fact that data is deleted after reboot is not really important in the discussed cases. This approach is very convenient because any installation has RAM available, thus no additional hardware is purchased. Thus, StarWind RAM Disk becomes an optimal solution for test and development, troubleshooting process or some niched deployments.
|StarWind HyperConverged Appliance is a turnkey, entirely software-defined hyperconverged platform purpose-built for intensive virtualization workloads. Bringing the desired performance and reducing downtime, the solution can be deployed by organizations with limited budgets and IT team resources. Also, it requires only one onsite node to deliver HA for your applications that make the solution even more cost-efficient.|
|Find out more about StarWind HyperConverged Appliance|
StarWind RAM Disk creates a high-performance virtual disk from RAM, offering a near-perfect solution for test and development scenarios, troubleshooting cases or other niched deployments, where size and data volatility don’t really matter.