The demand for real-time database is increasing. Indeed, most real-time systems are inherently distributed in nature and
need to handle data in a timely fashion. Obtaining data from remote sites may take long time making the temporal data invalid. This results in large number of tardy transactions with their catastrophic effect. Clustering the database sites nodes can help distributed real-time database systems to face the challenges meeting their time requirements. Reducing the large number of network sites into many clusters with smaller number of sites will effectively decrease the response time, resulting in better meeting of time constraints. In this paper, we introduce a clustering algorithm for distributed real-time database that depend on both the communication time cost and the timing properties of data. The results show the effectiveness of the proposed approach via achieving lower communication time, higher database performance and better meeting of timing requirements.