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Overview

While Twitter, Facebook and Snapchat garner the headlines, the explosion in data today is driven as much by machines as by humans.

Within machine data lies the single source of truth of customer activity, users, transactions, applications, servers, mobile devices and networks. Machine data is surprisingly dimensional. It includes configurations, API calls, change events, diagnostic commands, call detail records and sensor data from industrial systems and more.

Dimensionality, along with stunning volume and velocity confound traditional approaches to understand what is happening. CPU-powered solutions have bogged down in the face of this new challenge constraining the ability for organizations to diagnose service problems, thwart threats, understand the health and performance of networks and equipment and to comply with regulations.

The solution is not more servers, the solution is in different types of servers. Innovative organizations are turning to GPUs to solve their mission critical machine data tasks. MapD leverages just such hardware to dramatically accelerate the data discovery and exploration process - up to 1000x times faster than legacy CPU architectures.

Performance is what led, npm, Inc. the most widely used package manager for JavaScript to select MapD as their fast analytics platform. Npm hosts over a quarter million packages of reusable code and is used daily by over four million developers worldwide, who collectively download more than 4.5 billion packages every month. With more than 7 billion records of file data containing information such as date/timestamp, JavaScript package name, node and npm version number, proxy cache server point of presence (PoP), region - traditional analytical solutions took multiple minutes to return answers.

With MapD, however, npm was able to query the data in milliseconds, grasping exactly what was occurring within the Javascript community at any given moment - at a fraction of the cost of less performant solutions.

To find out how you can apply this computing paradigm to your problem, schedule a demonstration with our GPU experts and we can jointly determine if there is a fit.

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