MapD Big Data Management Powered by GPU Hardware


A young startup in San Francisco is an industry-leading example of what happens when big data meets the GPU: data processing at both very high speed and high volume. MapD, maker of the Core database system and Immerse data visualization system, is a database company designed around the use the special power of graphics processing units.

MapD is a sign that what used to be an add-on accelerator system is becoming more of a mainstream system that will be added to the data management systems that IT managers will have in their arsenal.

GPUs got their start as the hardware foundation for the display of video games, with their insatiable appetite for graphical processing. Because GPUs departed from the design of “Intel inside” servers, they had special capabilities when it came to big data jobs that could be processed in parallel. GPUs are good at seizing very large chunks of data and processing them in parallel in multiple threads. Intel’s x86 instruction set was originally geared to the single-thread, step-by-step processing of personal computing programs.

GPUs are getting their due as they are added to cloud servers or NoSQL data systems as accelerators. MapD skipped the accelerator phase and went straight to GPUs as the foundation for its data systems.

Todd Mostak, MapD’s founder and CEO, developed a prototype for a GPU-based database system while waiting on the outcome of his queries on hundreds of millions of tweets as he pursued research on the Arab Spring while at MIT. Each query took hours or days to complete and he wished he had his own cluster on which to perform them. He got the idea of combining a cluster of off-the-shelf video game cards with a new design for a parallel-processing database.

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