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A burst is an unusually large number of events occurring within a certain period of time. Various burst analysis methods over multiple window size have been proposed. However, real-time burst analysis is difficult owing to the huge amount of computation. This article proposes a method to analyze a burst in real-time. The proposed method reduces computation by avoiding redundant data updates of no event occurrence, and by suppressing data within a certain period in the case of emergent increase of events. In addition, a level and a rank of a burst can be analyzed simultaneously. The effectiveness of the proposed method is evaluated by experiments with real data. The result shows that the proposed method is more effective in analyzing real data, and more efficient in handling a large amount of events.