Abstract
Temporal graphs capture the relationships within data as they develop throughout time. Intuition, therefore, suggests that this model would fit naturally within a streaming architecture, where new points of comparison can be inserted directly into the graph as they arrive from the data source. However, the current state of the art has yet to join these two concepts, supporting either temporal analysis on static data or streaming into one-dimensional dynamic graphs. To solve this problem we introduce Raphtory, a temporal graph streaming platform, which maintains a full graph history whilst efficiently inserting new alterations.
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