We are proud to present “Where Database Technology Meets Model-Driven Engineering” with subtitle “Rethinking Internal Data Representation in Genus App Platform”, a master thesis from the Norwegian University of Science and Technology, NTNU, written by Håkon Åmdal and co-supervised by Genus.
The thesis builds on the pre-study “Implementation and Optimization Techniques for Business Discovery Products” also written by Håkon Åmdal, but the master thesis has a broader perspective: It aims at reevaluating how Genus App Platform and other platforms for Model-Driven Engineering should handle data internally, and see whether the storage formats and techniques from in-memory database technologies could be applied.
With this research, in Genus App Platform, column storage with dictionary encoding, bitpacking, and null pointer compression leads to a memory reduction of 67 % and a load time reduction of 36 % for the TPC-H inspired Data Mart Load Benchmark. Also, operations that are adjusted to utilize the column storage format sees a performance impact of one, two, and even three orders of magnitude compared to the original implementation. The new internal data representation in Genus App Platform does not significantly reduce transactional performance. Thus, by using Genus App Platform as a proof-of-concept, the work has shown how techniques used by read-optimized databases increase Model-Driven Engineering versatility by enabling such tools to handle and analyze large datasets.
The work has been supervised by Professor Svein Erik Bratsberg, with our colleague and Lead Technical Architect Einar Bleikvin as co-supervisor. The work is part of our ongoing co-operation with NTNU at many levels, from academic student organizations to the Department of Computer and Information Science. If you are a Master or PhD student interested in no-code / rapid application delivery / model-driven technology, please Contact Us for more information. You may also want to have a look at our Students page, where you will find information regarding Summer Internships, and Project and Master’s Theses.
Click the download link below to open the thesis. If you are interested in a demonstration of our flexible and interactive tool for exploring, analyzing and sharing data and insight with other end users, Genus Discovery, please Contact Us.