5th International Conference on Cloud and Big Data Computing (ICCBDC), pp. 8-14, ACM

A distinctive aspect of the current era is the ferocious amount of data that is generated and processed in a daily basis. There is no wonder that this epoch is generally characterized as the “Era of Big Data”. Thus, many enterprises and research initiatives strive to find a way to effectively and efficiently collect, store and analyze Big Data in order to improve their services and make efficient decisions. Those approaches refer to several domains such as healthcare, transportation, governance, or insurance. Towards this direction, in this paper we contribute into the selection of the most appropriate database for efficiently storing and retrieving Big Data. More specifically, taking into account the nature of Big Data and the main categories of databases that currently exist, three (3) NoSQL document-based databases were considered for this comparative study, namely the ArangoDB, the MongoDB and the CouchDB. The performance of these databases was measured based on specific metrics and criteria, including the total execution time for the same CRUD operations and their corresponding demands for resources, concluding to the most suitable database for storing Big Data.