As ITS technology evolves, very large volume of traffic data can be obtained in real-time. Traffic data are continuously produced and they can be considered as a kind of stream data. Currently, such traffic data are not maintained permanently because of the storage limitations of operational systems. Therefore, it was impossible to compare temporal historical patterns over long time periods. In this paper, we propose a traffic data management scheme, which can handle historical data as well as current data. The proposed scheme is based on the GALIS architecture, which is a cluster-based distributed computing system architecture that consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone. Some experimental results showing performance factors are also explained.