Kinetica Brings GPU Acceleration with SQL to Tableau

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by Angela Guess

A new press release states, “Kinetica, provider of the fastest GPU-accelerated database, today announced the availability of native integration with Tableau allowing users to simultaneously ingest, explore, analyze, and visualize data within milliseconds to make critical decisions and find efficiencies, lower cost, generate new revenue, and improve customer experience. ‘We are excited for Kinetica to join our partner program,’ said Todd Talkington, Director Tech Partners at Tableau. ‘GPUs are designed around thousands of small, efficient cores that are well suited to performing repeated similar instructions in parallel. This makes them well-suited for compute-intensive analytics workloads on large data sets.’”

The release goes on, “Tableau combined with Kinetica helps businesses: (1) Bring AI and BI Together. 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. (2) Deploy Location-Based Analytics. Kinetica natively manages geospatial data such as points, shapes, tracks, and labels and provides out-of-the-box functions for location-based analytics. Kinetica’s “Reveal” visualization framework enables interactive real-time data exploration in conjunction with GPU-accelerated rendering of maps and accompanying dashboards. With Kinetica and Tableau, business analysts can make faster decisions by visualizing and interacting with billions of data elements instantly.”

The list goes on, “(3) Perform Streaming Analytics. 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.”

Read more at Business Wire.

Photo credit: Kinetica

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