All the computer you need, with none of the expense or hassle of traditional scaling.

TidalScale's HyperKernel technology lets you quickly and easily deploy a Software-Defined Server that ensures you make the best and most flexible use of your IT resources.
How to Power through R, Spark & Python Data Science problems with Software-Defined Servers.
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Chances are, your data sets already are becoming larger than your existing computing resources can handle. Unless you're investing in new hardware or rewriting code to run across clusters, you're probably sizing your problem to fit the limits of your server -- not the way to arrive at insights quickly.

TidalScale's Software-Defined Server technology has the answer. A revolution in scalability, Software-Defined Servers pool multiple commodity systems into a single virtual system that matches the size of your computer to the size of your data problem.

Fast, flexible and easy scaling with TidalScale HyperKernel. Deploy your own Software-Defined Servers using TidalScale's HyperKernel software.

How it works. HyperKernel works between your stock OS and bare metal hardware allowing you access to the combined resources (memory, CPUs, storage and network) of multiple commodity servers - all as a single system. We support a range of operating systems including Linux-based distributions (Red Hat Enterprise, Ubuntu, and CentOS) and FreeBSD.

Fast, easy and flexible. What's more, the TidalScale HyperKernel lets you run a single instance of your OS and application without requiring a single change to either. No investments in new hardware, no recoding to shard applications across machines, and no more settling for limiting the size of the data to the constraints of limited hardware resources. Just on-demand flexiblity to use resources as your applications demand, so even the biggest data problems don't bring your operations to a halt.

Discover what this means for:


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