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Alex Şuhan

Back when we started the current incarnation of the MapD Core database, we wrote our own parser (written using flex and GNU bison), semantic analysis and optimizer. This approach offers the most control since everything in the pipeline can be adjusted to the unique needs of our system, but we've realized that our main strength lies in the actual execution of the queries. In the context of the limited resources of a startup, we have to pick our battles. We soon faced a dilemma... read more

This post can also be found on Nvidia's site. 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. Although MapD is fast running on x86-64 CPUs, our real advantage stems from our ability to leverage the massive parallelism and memory bandwidth o... read more

Note: The following post was originally published on June 23, 2015 on Nvidia's Parallel ForAll blog. This is only an excerpt, you can find the full original here. Co-written by Alex Suhan and Todd Mostak of MapD. 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... read more