H2O.ai is releasing an enhanced version of its Sparkling Water platform with additional features and boosted functionality.
New features in Sparkling Water 2.0 include the ability to interface with Apache Spark, Scala, and MLlib via H2O.ai's Flow UI, build ensembles using algorithms from both H2O and MLlib, and give Spark users the power of H2O's visual intelligence capabilities.
Other improvements include support for Apache Spark 2.0 and backwards compatibility with all previous versions, support for the Apache Zeppelin notebook, H2O feature improvements and visualizations for MLlib algorithms, visual intelligence for Apache Spark, the power to export MLlib models as POJOs (Plain Old Java Objects), a toolchain for building machine learning pipelines on Apache Spark, production support for machine learning pipelines and the operationalization of MLlib through H2O scoring engines, real-time machine learning for data products using Spark Streaming and H2O, and model and data governance through Steam.
Sparkling Water was designed to allow users to get the best of Apache Spark -- its elegant APIs, RDDs and multi-tenant Context -- along with H2O's speed, columnar-compression, and fully-featured machine learning algorithms. Sparkling Water also allows for greater flexibility when it comes to finding the best algorithm for a given use case.
"Beauty and functionality are essential to everything we do at H2O.ai," said Sri Ambati, H2O.ai CEO. "We're totally committed to the open source movement and doing everything we can to bring visually appealing, and easy to comprehend, AI-driven insights to enterprise users."
For more information about Sparkling Water 2.0, visit www.h2o.ai.