Real-Time Analytics with an In-Memory, GPU-Accelerated Database

Salon E
Streaming Data

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.

Speakers
John
Lynch
Principal Field Engineer
at
Kinetica
John Lynch is Principal Field Engineer at Kinetica. Previously, John worked at Cloudera, where he was a Senior Systems Engineer. At Cloudera, John spent the last 2 years working with a major bank, modernizing their Risk Modeling Environment (~6000 Hadoop nodes). Additionally, John worked in LATAM landing deals at various financial organizations. Prior to Cloudera, John worked as a Master Principal Consultant at Oracle (through Endeca Acquisition). John was alsoo both Lead Solution Architect and Director, Tech Sales at Fast Search And Transfer (acquired by MSFT). John earned a Bachelors degree from Illinois State University.

Slides

Recording