Can the elephants handle the NoSQL onslaught?

TLDR

Traditional RDBMSs are being challenged by both document‑store NoSQL systems like MongoDB and big‑data analytics platforms such as Hive on Hadoop. The study compares a representative NoSQL system from each end of the spectrum with SQL Server to evaluate performance and scalability on decision‑support and interactive data‑serving workloads. The authors benchmarked one NoSQL system per spectrum end against SQL Server, measuring performance and scalability across decision‑support and interactive data‑serving workloads. The evaluation reveals insights into the relative strengths of NoSQL and SQL, suggesting future trends in big‑data database adoption.

Abstract

In this new era of "big data", traditional DBMSs are under attack from two sides. At one end of the spectrum, the use of document store NoSQL systems (e.g. MongoDB) threatens to move modern Web 2.0 applications away from traditional RDBMSs. At the other end of the spectrum, big data DSS analytics that used to be the domain of parallel RDBMSs is now under attack by another class of NoSQL data analytics systems, such as Hive on Hadoop. So, are the traditional RDBMSs, aka "big elephants", doomed as they are challenged from both ends of this "big data" spectrum? In this paper, we compare one representative NoSQL system from each end of this spectrum with SQL Server, and analyze the performance and scalability aspects of each of these approaches (NoSQL vs. SQL) on two workloads (decision support analysis and interactive data-serving) that represent the two ends of the application spectrum. We present insights from this evaluation and speculate on potential trends for the future.