Archive and Restore of Complex Data with Support of Schema Evolution
Bachelor Thesis
Leon Büttinghaus
More and more often, modern software must deal with large amounts of data which have to be maintained and organized. Therefore, the live databases of such applications must be able to read, write and update many tuples of data as fast as possible. In a world where the volume of data is growing exponentially, solutions for keeping a live database as efficient as possible are needed more than ever.
One way to keep the database efficient is to outsource data, which is not used anymore. But instead of completely deleting it, the data can be archived, for data retention reasons or in the case that it is needed again in the future.
One of the main challenges of archive systems occurs, when archived data must be restored back into the software's live database, which might have evolved over the time. So, the archive system must support Schema Evolution, the process of a changing database schema and its elements.
The goal of this bachelor thesis is to examine different approaches of archiving methods and evaluate them, regarding their advantages and disadvantages. Another goal is to compare possible solutions for handling Schema Evolution and to work out ways to embed such solutions into an archive system. In the end, this thesis aims to provide the concept of an archiving system fitting the requirements of an exemplary application and its live database.