Having made the improbable jump from the game console to the supercomputer, GPUs are now invading the datacenter. This movement is led by Google, Facebook, Amazon, Microsoft, Tesla, Baidu and others who have quietly but rapidly shifted their hardware philosophy over the past twelve months.

As we enter the final stretch of our summer, it is time to start looking ahead to the conference-rich third and fourth quarters. After a period of relative calm, we are back with a vengeance, starting almost immediately.

In the dataworld, there is a particular dataset, referred to as “the taxi dataset,” that has been getting a disproportionate amount of attention lately.

Who would have thought that analytics would become the bottleneck in the modern organization?

There is little question that the GPU age is upon us. We see it everywhere, from game consoles to supercomputers and now the datacenter, GPUs are permeating more and more of the computing ecosystem.

MapD was built from the ground up to enable fully interactive querying and visualization on multi-billion row datasets. An important feature of our system is the ability to visualize large results sets, regardless of their cardinality

MapD is a next-generation data analytics platform designed to process billions of records in milliseconds using GPUs. It features a relational database backend with advanced visualization and analytic features to enable hyper-interactive exploration of large datasets.

It’s nice to be cool, particularly when the folks naming you cool are none other than the esteemed team at Gartner. It is why we are so excited that Gartner chose MapD as a Cool Vendor in DBMS.

At MapD our goal is to build the world’s fastest big data analytics and visualization platform that enables lag-free interactive exploration of multi-billion row datasets. MapD supports standard SQL queries as well as a visualization API that maps OpenGL primitives onto SQL result sets.