Identification of influential nodes in complex networks is crucial in many applications. Hierarchy and centrality are two principal approaches to quantify the influence of a node. Although there has been a lot of work about the relationship between centrality measures, to our knowledge there is no study to characterize the interplay between hierarchy and centrality measures. In this paper, based on a collection of real-world networks originating from diverse domains, a comparative investigation is performed. Results indicate that hierarchy and centrality measures are more or less complementary according to the network structure. More precisely, density and transitivity drive the redundancy of information between both types of measures. Additionally, nested hierarchy measures are the most orthogonal to the centrality measures under study.