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This week we release version 3.1 of MapD, which comes after some truly giant news over the last few weeks, and adds a number of useful new features. First, we’ve brought into Immerse a feature from the MapD Core Rendering Engine called Density Gradient, which helps you spot areas of concentration when you’re looking at visualizations of big data. For example, let’s say you’re looking at the New York City street grid and trying to find the heaviest areas of taxi drop-offs. B... read more

The MapD Immerse visual analytics client has a core feature we refer to as crossfilter, which allows a filter applied to one chart to simultaneously be applied to the rest of the charts on a dashboard. This provides a natural interface for data exploration, allowing a multi-dimensional view of data even as a user drills deep into a dataset. From a technical perspective, crossfiltering is not difficult (on the surface). Behind each Immerse chart is a SQL statement. When an e... read more

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. Ordinary BI systems do fine when rendering standard bar or pie charts but often fall over when required to render the millions of records often associated with scatter plots, network graphs and various forms of geovisualization. Being able to... read more

A few years back, the American Statistical Association put out a dataset of hundreds of millions of US airline flights from 1987 to 2008, as part of a supercomputing competition. The dataset includes every single flight record known by Bureau of Transportation Statistics for that two decade period; every prop plane, every jet plane, balloon or blimp. We wanted to put the MapD database and visualization software through its paces, as well as help you figure out whether your l... read more