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Kinetica Blog

Amit Vij | August 2, 2017

12 Features to Look for When Choosing a GPU-Accelerated Analytics Database

GPU acceleration is revolutionizing high-performance computing. Leveraging GPUs for processing-intensive workloads is on the rise, particularly among verticals such as finance, retail, logistics, health/pharma, and government....
Richard West | July 19, 2017

How GlaxoSmithKline Uses Kinetica to Manage Their R&D Information Platform

Mark Ramsey, SVP, R&D Data, at GlaxoSmithKline, spoke at a recent IBM/Kinetica executive breakfast, where he discussed how GSK uses GPUs and Kinetica to help transform the way that data is used as a strategic asset within their R&D organization....
Michele Nemschoff | July 7, 2017

Five examples where GPU databases are bringing ‘real-time’ to IoT analytics

If your organization manages large volumes of streaming IoT data, you’ll no doubt be familiar with some of the challenges of getting value and insight from these high volume, moving datasets....
Amit Vij & Nima Negahban | June 29, 2017

Kinetica Secures Series A Investment of $50 Million

Today we’re pleased to announce that Kinetica has closed a $50M Series A funding round....
Karthik Lalithraj | June 21, 2017

Bring Your Own Compute (BYOC) – How In-database Analytics on the GPU Unlocks the Potential of Machine Intelligence in Finance

Compute analytics in financial services have evolved over the past decade. Popular tools for forecasting and assessing risk like statistical functions involving linear regression, logistic regression have given way to more sophisticated models....
Manan Goel | June 13, 2017

TensorFlow bundled with Kinetica – Distributed deep learning now available to the enterprise

Today, we’re excited to announce that TensorFlow™ — the industry’s leading open-source library for machine intelligence — now comes bundled with Kinetica....
Ben Campbell | May 12, 2017

How Does a GPU Database Play in Your Machine Learning Stack?

Machine learning (ML) has become one of the hottest areas in data, with computational systems now able to learn patterns in data and act on that information....
Manan Goel | May 12, 2017

“ETL is dead” – Five Big Statements from Kafka Summit

This week, over 500 technologists – from enterprises such as BNY Mellon, Goldman Sachs, Google, ING, Target and many more – came together at Kafka Summit to learn and share tips in working with and getting value from high-speed data....
James Dilworth | May 1, 2017

Machine Learning and Predictive Analytics in Finance: Observations from the Field

Financial institutions have long been on the cutting edge of quantitative analytics....
Michele Nemschoff | April 24, 2017

8 Trends in High-Performance Analytics – Insights from Forrester

Forrester, as a guest of Kinetica, held a webinar this month about how digital business is driving rapid expansion and sophistication of data and insight, and why it’s necessary to augment traditional CPU-bound analytics with GPUs, in-memory processing, and machine learning....