Abstract Existing spatiotemporal indexes suffer from either large update cost or poor query performance, except for the Bx -tree (the state-of-the-art), which consists of multiple B+ -trees indexing the 1D values transformed from the (multi-dimensional) moving objects based on a space filling curve (Hilbert, in particular). This curve, however, does not consider object velocities, and as a result, query processing with a Bx -tree retrieves a large number of false hits, which seriously compromises its efficiency. It is natural to wonder "can we obtain better performance by capturing also the velocity information, using a Hilbert curve of a higher dimensionality?". This paper provides a positive answer by developing the Bdual -tree, a novel spatiotemporal access method leveraging pure relational methodology. We show, with theoretical evidence, that the Bdual -tree indeed outperforms the Bx -tree in most circumstances. Furthermore, our technique can effectively answer progressiv...