The sequential pattern mining on progressive databases is comparatively very new, in which progressively find out the sequential patterns in time of interest. Time of interest is a sliding window which is continuously move forwards as the time goes by. As the focus of sliding window changes, the new items are added to the dataset of interest and obsolete items are removed from it and become up to date. In previous pattern mining techniques sequential patterns are generated, the newly arriving patterns may not be identified as frequent sequential patterns due to the existence of old data and sequences. Progressive databases have posed new challenges because of the following innate characteristics such as it should not only add new items to the existing database but also removes the obsolete items from the database. The proposed tree based approach efficiently overcomes the inconsistencies in the existing methodologies and the execution time also prominent good for huge databases.

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Progressive Database Time Of Interest Ps-tree Fast Pisa Algorithm