Many current database systems use some form of histograms to approximate the frequency distribution of values in the attributes of relations and based on them estimate some query result sizes and access plan costs. In this paper, we overview the line of research on histograms that we have followed at the Univ. of Wisconsin. Our goal has been to identify classes of histograms that combine three features in most realistic cases: (i) they produce estimates with small errors, (ii) they are inexpensive to construct, use, and maintain, and (iii) they can be used for many diverse estimation problems. Based on that goal, we present several results, which eventually point towards a class of histograms that are practical, close to optimal, and effective in estimating sizes of query results, frequency distributions of attribute values in query results, and even costs of accesses using secondary indices.