Using a single type of database solution to support real-world applications is becoming more and more challenging because of the volume and variety of data. For instance, the data collected for the transportation industry comprise both structured and unstructured data. Using solely a single type of database solution—relational database system-only or graph database-only—to store and manage data can be challenging. As real-world applications ask even more complex questions related to data, the database solution should be able to facilitate answering these questions in a reasonable time. Hence, in this paper, we present a hybrid model, which integrates data to support transportation analytics. The model consists of relational databases and non-relational databases (namely, graph databases), pooling their strengths to support the demands of the modern application. We also demonstrate this hybrid data model as a practical solution with a case study on improving emergency services—such as emergency medical services (EMS)—response times by having the support of the presented platform.