Real-Time Analytics with an In-Memory, GPU-Accelerated Database
As enterprises look to extract business value from the massive volume, variety, and velocity of public and proprietary data, they need faster, easier, and richer data, analytics, and visualizations to explore data at scale and speed to discover game-changing insights. Modern big data analytics systems have evolved to take advantage of data-in-motion and data-at-rest with cost-efficient scale-out storage, faster networks and larger amounts of memory. Freed from the constraints of storage, network and memory, these systems now routinely reveal themselves to be compute-bound. To compensate, big data analytic systems often result in wide horizontal sprawl.
In this talk, you’ll learn about a new groundbreaking in-memory database technology that’s powered by GPUs which enables high-speed data ingest and real-time data queries and analytics. Drawing from real-world production use cases and live demos, Kinetica VP Mate Radaljj will demonstrate how it’s possible to perform advanced analytical queries across billions of rows of data in milliseconds. Mate will also provide ROI comparisons using real-world, deployed use cases in a wide variety of verticals.