In this paper we deal with the real time processing and visualization of data streams. In order to deal with data streams we propose a novel approach that uses a neighborhood-based clustering. Instead of processing each new element one by one, we propose to process each group of new elements simultaneously. A clustering is applied on each new group using neighborhood graphs. The obtained clusters are then used to construct incrementally a representing graph of the data stream. The data stream graph is visualized in real time with specific visualizations that reflects the processing algorithm. To validate the approach, we apply it to multiple data sets and we compare it with various stream clustering approaches.