Final Thesis: Modernizing the Data Storage Interface of a Cloud Application
Abstract: This thesis presents the modernization of the backend architecture of QDAcity, a cloud-based web application that supports Qualitative Data Analysis (QDA). The existing backend of QDAcity is effective; however, it has limitations in terms of efficiently handling blob data, which can affect both performance and scalability. In order to address these challenges, the project introduces a new storage infrastructure, which serves to improve the management and organization of blob data associated with qualitative research. Moreover, the thesis presents a restructuring of the Datastore Application Programming Interface (API) with the objective of optimizing the system’s performance and streamlining its interactions with the data. The principal enhancements include the flexibility of entity structures to support multiple blobs per entity, which is indispensable for more intricate data scenarios. In addition to these changes, the project implements strategies for better resource allocation and reduces latency in data retrieval, ensuring smoother operations. This comprehensive overhaul not only guarantees a more maintainable and scalable backend but also establishes the foundation for prospective extensions and improvements in the QDAcity platform.
Keywords: Google Cloud, Datastore, Objectify, Qualitative Research, QDAcity
PDF: Bachelor Thesis
Reference: Jan Michael Rehnert. Modernizing the Data Storage Interface of a Cloud Application. Bachelor Thesis. Friedrich-Alexander-Universität Erlangen-Nürnberg: 2024.