Evaluation of key-value databases for the storage of large process mining event logs

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Alessandro Berti

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+49 241 80 21949

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BSc Thesis Project

Title: Evaluation of key-value databases for the storage of large process mining event logs

Author: Niklas Schulte

Supervisor: Alessandro Berti

1st examiner: Prof.Dr. ir. Wil M.P. van der Aalst

2nd examiner: Prof. Dr.-Ing Ulrik Schroeder

Summary

Key-value databases are a fast and flexible storage solution. As the amount of process mining data increases constantly and new fields of process mining arise, appropriate storage solutions are necessary. Therefore, we investigated in key-value databases as a storage solution for large process mining event logs in this thesis. We have elaborated a method of storing event data in a key-value fashion and implemented two event stores in Python on top of these. An evaluation is performed with three real-life event logs on different aspects such as importing and exporting data as well as the ability to provide data samples in various orders of access.