Kinetica Brings GPU Acceleration to Tableau

Kinetica, a provider of GPU-accelerated database technology, is introducing native integration with Tableau.

According to the companies, Tableau combined with Kinetica helps organizations in a number of ways. Kinetica’s open architecture features a user-defined functions (UDFs) framework to extend database functionality, enabling developers and data scientists to deploy custom code, open source, and advanced machine learning libraries natively within the database as GPU-accelerated business logic to power advanced business analytics.

 Kinetica also natively manages geospatial data such as points, shapes, tracks, and labels and provides out-of-the-box functions for location-based analytics. Its “reveal” visualization framework enables interactive real-time data exploration in conjunction with GPU-accelerated rendering of maps and accompanying dashboards, enabling business analysts to make faster decisions by visualizing and interacting with billions of data elements.

Kinetica’s in-memory database is designed to take advantage of the parallel processing nature of the GPU for streaming analytics on large, complex real-time data from sensors, connected devices, social media, and mobile apps. Kinetica features connectors for Apache Kafka, Apache Nifi, Apache Storm, and Apache Spark and ingests large, complex data in parallel making streaming data available for query and analytics in real-time on Tableau.

And finally, Tableau’s “replace data source” feature ensures users can take advantage of Kinetica’s speed and advanced analytics without any changes to existing Tableau workbooks. Users can point Tableau workbooks to Kinetica and leverage Kinetica’s ODBC and JDBC connectivity along with SQL-92 support to accelerate Tableau workbooks.

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