Architectural assessment of NoSQL and NewSQL systems

With the recent trend towards big data, a number of scalable data management systems: NoSQL and NewSQL are developed to manage massive data effectively. The algorithms involved in the architectural design of a data management system defines the response time of an application. The behavior and performance of different NoSQL and NewSQL systems vary on the basis of these architectural aspects. Hence, the architectural assessment of a data management system is a vital task to perform in order to understand their weaknesses and strengths. Therefore, this paper assesses the architecture of some well-known NoSQL and NewSQL systems in detail. To enhance the clarity of discussion and analysis, we identified and grouped together the logically related architectural features, forming a feature vector (FV). Feature vectors related to transactional properties, fault tolerance, data storage, and data handling are designed and involved in architectural assessment. Various significant features are identified and assigned to a feature vector. Some well-known NoSQL and NewSQL systems are analyzed, compared, and discussed in depth with respect to these feature vectors. The discussion involves describing the algorithms used in implementation of a particular architectural feature by each of the systems and their suitability analysis in various scenarios. Important guidelines are presented that helps in filtering the potential data management systems on the basis of application requirements.