Public Knowledge Graphs (KGs) on the Web are considered a valuable asset for developing intelligent applications. They contain general knowledge which can be used, e.g., for improving data analytics tools, text processing pipelines, or recommender systems. While the large players, e.g., DBpedia, YAGO, or Wikidata, are often considered similar in nature and coverage, there are, in fact, quite a few differences. In this paper, we quantify those differences, and identify the overlapping and the complementary parts of public KGs. From those considerations, we can conclude that the KGs are hardly interchangeable, and that each of them has its strenghts and weaknesses when it comes to applications in different domains.