Quantitative Analysis of Scalable NoSQL Databases

Abstract

NoSQL databases are rapidly becoming the customary data platform for big data applications. These databases are emerging as a gateway for alternative approaches outside traditional relational databases and are characterized by efficient horizontal scalability, schema-less approach to data modeling, high performance data access, and limited querying capabilities. The lack of transactional semantics among NoSQL databases has made the choice of a particular consistency model dependent on the application. Therefore, it is essential to examine methodically, and in detail, the performance of various databases under diverse workload conditions. Three of the most commonly used NoSQL databases: MongoDB, Cassandra and HBase are evaluated using the Yahoo Cloud Service Bench-mark, a popular benchmark tool. The horizontal scalability of the three systems under different workload conditions and varying dataset sizes is captured. A benchmark suite which summarizes the results of the evaluation is presented.