  Many industries rely on visual insights to support decision- making processes
in their businesses. In mining, the analysis of drills and geological shapes,
represented as 3D geometries, is an important tool to assist geologists on the
search for new ore deposits. Aeronautics manipulate high-resolution geometries
when designing a new aircraft aided by the numerical simulation of
aerodynamics. In common, these industries require scalable databases that
compute spatial relationships and measurements so that decision making can be
conducted without lags. However, as we show in this study, most database
systems either lack support for handling 3D geometries or show poor performance
when given a sheer volume of data to work with. This paper presents a pluggable
acceleration engine for spatial database systems that can improve the
performance of spatial operations by more than 3000x through GPU offloading. We
focus on the design and evaluation of our plug-in for the PostgreSQL database
system.
