Recent works in sparse direct solvers have multiplied the solutions to exploit data-sparsity additionally to sparse structure in these solvers. Among these solution, the PaStiX solver exploits block low-rank structures to reduce both its memory consumption and time to solution. In this talk, we will discuss recent changes made to the solver in this context such as the study of suitable low-rank compression kernels, adapted ordering heuristics, or scheduling strategies through the use of runtime systems. Performance results of the latest release including the presented features will be shown and discussed.