The purpose of this study was to find out which demands are put on a DBMS, database management system, powering a recommendation service, what impact the NoSQL databases have on the performance of recommendation services compared to traditional relational databases, and which DBMS is most suited for storing the data needed to host a recommendation service.
Five distinct NoSQL and Relational DBMS were examined, from these three candidates were chosen for a closer comparison. Following a study of recommendation algorithms and services, a test suite was created to compare DBMS performance in different areas using a data set of 100 million ratings.
The results show that MongoDB had the best performance in most use cases, while Neo4j and MySQL struggled with queries spanning the whole data set. This project however never compared performance for real production code. To get a better comparison, more research is needed. We recommend new performance tests for MongoDB and Neo4j using implementations of recommendation algorithms, a larger data set, and more powerful hardware.
Authors: Chavez Alcarraz, Erick | Moraga, Manuel