Nvidia Blog - The MapD database uses GPUs to process SQL queries in parallel across nearly 40,000 cores per server, yielding massive speedups over leading in-memory databases. When paired with the MapD Immerse analytics front-end, the system delivers instant visual insights into datasets with billions of records

Bloomberg - MapD’s technology -- a database and a visual analytics system -- helps customers sift through and compare data quickly. The company uses what’s called graphics processing units, or GPUs, which are often used in computer gaming, and are faster than the central processing units traditionally used to power database systems.

Barron’s - The innovation in MapD’s case is to use many, many GPUs, which makes it possible to store many tables in memory, which means scaling massively parallel collections of GPU cores will rise and rise...

Fortune - MapD, a startup that’s pressing graphics processors into service to speed up both number crunching and analytics of those numbers, now has $10 million in fresh funding to build up its engineering staff.

Market Wire - Alston to Lead Go-to-Market Strategy for MapD's Big Data, Analytics and Visualization Platform

US News & World Report - Between 1989 and 2014, Trump donated a total of $1,219,950, according to data from the Center for Responsive Politics, obtained through the Sunlight Foundation. The video below, courtesy of MapD, a GPU-powered database and visualization platform for interactive data analytics, shows his ever-changing political allegiance.

Fortune - With GPUs getting more memory, Mostak realized that the Intel and AMD part of the database can now take a backseat to the graphics processors because the GPUs finally have the memory capabilities to store the data as it’s being processed.

eWeek - Startup MapD has been using Tesla K80 accelerators on IBM Cloud for data and analytics. The solution enables multiple users to query and visualize multi-billion row data sets with latencies measured in milliseconds, achieving orders-of-magnitude increases in speed over other solutions

Nvidia Blogs - Fast hardware is only half of the story, so at MapD we have invested heavily into optimizing our code such that a wide range of analytic workloads run optimally on GPUs. In particular, we have worked hard so that common SQL analytic operations, such as filtering (WHERE) and GROUP BY, run as fast as possible.

VentureBeat - MapD uses graphics processing units (GPUs) to crunch Big Data — the sort that usually only rooms full of servers are able to do, but \“at a fraction of the price of what a big cluster [of servers] would cost, with much greater performance.\"