Unlike traditional tree-based indexes that are blind to the possible regularity present in the input data, the PGM-index exploits a learned mapping between the indexed keys and their location in memory. The succinctness of this mapping, coupled with a peculiar recursive construction algorithm, makes the PGM-index a data structure that dominates traditional indexes by orders of magnitude in space while still offering the best query and update time performance.
In addition to that, the PGM-index offers compression, distribution-awareness, and multi-criteria adaptability, thus resulting suitable for addressing the increasing demand for big data systems that adapt to the rapidly changing constraints imposed by the wide range of modern devices and applications.