For over forty years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have emerged, namely NoSQL technology. The rising interest in NoSQL technology, as well as the growth in the number of use case scenarios, over the last few years resulted in an increasing number of evaluations and comparisons among competing NoSQL technologies. While most research work mostly focuses on performance evaluation using standard benchmarks, it is important to notice that the architecture of real world systems is not only driven by performance requirements, but has to comprehensively include many other quality attribute requirements. Software quality attributes form the basis from which software engineers and architects develop software and make design decisions. Yet, there has been no quality attribute focused survey or classification of NoSQL databases where databases are compared with regards to their suitability for quality attributes common on the design of enterprise systems. To fill this gap, and aid software engineers and architects, in this article, we survey and create a concise and up-to-date comparison of NoSQL engines, identifying their most beneficial use case scenarios from the software engineer point of view and the quality attributes that each of them is most suited to.

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The continuous information growth in current organizations has created a need for adaptation and innovation in the field of data storage. Alternative technologies such as NoSQL have been heralded as the solution to the ever-growing data requirements of the corporate world, but these claims have not been backed by many real world studies. Current benchmarks evaluate database performance by executing specific queries over mostly synthetic data. These artificial scenarios, then, prevent us from easily drawing conclusions for the real world and appropriately characterize the performance of databases in a real system. To counter this, we used a real world enterprise system with real corporate data to evaluate the performance and space characteristics of popular NoSQL databases and compare them to SQL counterparts. We present one of the first write-heavy evaluations using enterprise software and big data. We tested Cassandra, MongoDB, Couchbase Server and MS SQL Server, comparing their performance and total used space while handling demanding and large write requests from a real company with an electrical measurement enterprise system.

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