xPatterns Delivers Apache Spark 1.6 for Enterprise at the Speed of Now

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Atigeo_logoAtigeo™, a technology company and developer of the xPatterns® big data analytics platform and cyber and healthcare analytics solutions, has migrated enterprise-grade Apache Spark 1.6 to its platform distribution, allowing customers immediate availability and seamless integration into the rest of their technology stack.

We keep our customers at the forefront of big data and data science technology, without compromise on enterprise-grade reliability, security and support. We continually deliver these emerging technologies to provide their latest benefits, without lag or the complexities of integration,” said David Talby, chief technology officer of Atigeo.

The Spark 1.6 migration provides substantial performance advances to xPatterns. As the only continuously self-improving, vertically integrated big data platform, xPatterns has a feedback loop to inform prediction – across query processing, data ingestion, data wrangling and data science, at scale. The deep integration of Spark across all layers of the xPatterns platform immediately provides the benefits of Spark 1.6 enhancements such as:

  • automated memory configuration,
  • Apache Parquet performance improvements,
  • unified memory management,
  • enriched query planning, and adaptive query execution.

xPatterns apps also support direct access to the full Spark API, providing the enhanced Python and R API capabilities of Spark 1.6. Python APIs have been greatly enhanced within 1.6 for feature parity with Scala, and SparkR now supports a feature interaction operator in R formulae, as well as R-like statistics for ordinary least squares.

These improvements are transparent to our xPatterns customers. The parallel data ingestion, data transformation, distributed query and data publishing components of xPatterns are updated for 1.6, so xPatterns applications that use the user interface or z of these components will just work faster going forward,” continued Talby.


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