There are a wide number of graph centrality metrics. Further, the performance of each can vary widely depending on the type of implementation. In this work we present our implementation of triangle centrality in Arkouda with several different triangle counting methods. Triangle Centrality is a robust metric that captures the centrality of a vertex through both a vertex’s own connectedness and that of its neighbors. Arkouda is an open-source framework for data science at the scale of terabytes and beyond. These methods are compared against each other and another shared memory implementation.