A graph is a structure composed of a set of vertices (i.e. nodes, dots) connected to one another by a set of edges (i.e. links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval paradigm. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free traversals. This presentation will discuss the graph traversal programming pattern and its application to problem-solving with graph databases.