3 posts found under,

rendering

Continuing where we left off in our earlier post on MapD 2.0’s Immerse visualization client, today we want to walk you through some of version 2.0’s major improvements to our GPU-accelerated Core database and Iris Rendering Engine. Before we delve into the details, main themes for this release are: speed, robustness, and further visual analytics power. Our system is able to steadily deliver extremely fast query speeds across a larger set of SQL queries and when analyzing dat... 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

While we love datasets of all shapes and sizes at MapD, Twitter holds a special place in our hearts. This is perhaps because we find Twitter data to be almost peerless among public datasets in its ability to provide a glimpse into the human experience - revealing what people are saying when and where. Twitter is powerful in that it provides insight into a wide variety of social phenomena both at the level of individual tweets as well as rolled up by user, geography or topic/... read more