Data Science Made Easy

Have you hit the limitations of R when trying to understand large data? Are you frustrated by having to port your R prototype into Python or Spark when moving into production with full size data set?

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If you’ve been limiting the size of your problems and models to fit your available computing resources, then it’s time to investigate Software-Defined Servers. A TidalScale Software-Defined Server lets you continue to scale your work in R without any changes to your code.

  • In-memory performance at any scale - Software-Defined Servers deliver in-memory performance at any scale. They’re self-optimizing, use standard hardware, and are compatible with all applications and operating systems.
  • No more compromises - With Software-Defined Servers from TidalScale, there’s no more paring back the breadth of your analysis, no more waiting for results, and no more rewriting code to run applications across clusters.

As the leading provider of Software-Defined Servers, TidalScale is making it possible for more organizations to draw insights from big data faster, more easily, and with greater flexibility than ever before. Download the TidalScale Performance white paper on Open Source R to see for yourself.

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