Data Resilience in PolyDBMS Systems (Bachelor Thesis, Finished)


Flurina Fischer


The digital age has witnessed an unprecedented explosion in data production, creating a pressing need for advanced data management systems capable of handling the diverse and increasingly heterogeneous nature of data. This surge has led to the emergence of various data management systems, each designed to meet specific data processing requirements. PolyDBMS are particularly notable in this landscape, as they offer multiple data models and support a wide array of underlying databases to cope with the complexities of modern data ecosystems. However, despite their versatility, PolyDBMS systems currently suffer from a critical shortcoming: they lack robust backup and restore mechanisms, which leaves valuable data vulnerable to loss or corruption. The diverse and complex data landscape managed by PolyDBMS systems requires a backup and restore solution that can handle intricate schema structures, diverse data models, and systematic elements unique to PolyDBMS. Existing backup and restore mechanisms may not be sufficient to ensure data resilience in such a context.

The objective of this thesis is to design and implement a suitable backup and restore architecture tailored to the specific challenges posed by PolyDBMS, with a focus on the Polypheny system.

Start / End Dates

2023/09/13 - 2024/01/12


Research Topics