In recent years, maintaining the history of graphs has become increasingly imperative due to the emergence of related applications in several fields, like health services, social interactions, and map guidance. Historical graphs focus on being able to store and query the whole graph evolution and not just the latest instance. Various frameworks have been used to store these graphs and query them. In this paper, we look at how an evolving historical graph can be stored in the distributed SQL database CockroachDB focusing on OLAP queries. In particular, we study an OLAP query (time-interval degree distribution) as to how it can be better executed in a distributed environment to improve its efficiency. To this end, we provide different approaches for this particular query that have different trade-offs between local computation and network latency. Finally, we provide experimental evidence concerning these trade-offs.