A social network evolves over time through the creation or deletion of ties among a set of actors.The volatile nature of social ties provides a strong platform to identify the dynamic network structure. This change of structural patterns can be well represented by the existence of dynamic graph objects Further, they can be enriched with the temporal information of social ties to define the recurrent subgraphs of interest. This would yield important insights about the correlation between patterns of ties in a social network. Major contribution of our study is the proposal and implementation of a scalable data structure to handle online and offline dynamic network objects. Hence, it can be used for large scale graph modeling, analysis and visualization purposes.