Trees or grids?: indexing moving objects in main memory

New application areas, such as location-based services, rely on the efficient management of large collections of mobile objects. Maintaining accurate, up-to-date positions of these objects results in massive update loads that must be sup-ported by spatial indexing structures and main-memory in-dexes are usually necessary to provide high update perfor-mance. Traditionally, the R-tree and its variants were used for indexing spatial data, but most of the recent research assumes that a simple, uniform grid is the best choice for managing moving objects in main memory. We perform an extensive experimental study to compare the two approaches on modern hardware. As the result of numerous design-and-experiment iterations, we propose the update- and query-efficient variants of the R-tree and the grid. The experiments with these indexes reveal a number of interesting insights. First, the coupling of a spatial in-dex, grid or R-tree, with a secondary index on object IDs boosts the update performance significantly. Next, the R-tree, when combined with such a secondary index, can pro-vide update performance competitive with the grid. Finally, the grid can compete with the R-tree in terms of the query performance and it is surprisingly robust to varying param-eters of the workloads. In summary, the study shows that, in most cases, the choice of the index boils down to the is-sues such as the ease of implementation or the support for spatially extended objects