Improving the Performance of the Eiffel Event Persistence Solution

Abstract: Deciding which database management system (DBMS) to use has perhaps never been harder. In recent years there has been an explosive growth of new types of database management systems that address different issues and performs well for different scenarios. This thesis is an improving case study of an Event Persistence Solution for the Eiffel Framework, which is a framework used for achieving traceability in very-large-scale systems development. The purpose of this thesis is to investigate whether it is possible to improve the performance of the Eiffel Event Persistence Solution by changing from MongoDB, to Elasticsearch or ArangoDB. Experiments were conducted to measure the request throughput for 4 types of requests. As a prerequisite to measuring the performance, support for the different DBMSs and the possibility to change between them was implemented. The results showed that Elasticsearch performed better than MongoDB in terms of nested-document-search as well as for graph-traversal operations. ArangoDB had even better performance for graph-traversal operations but had an inadequate performance for nested-document-search.