Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have\nresulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that\npromises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on\ndata management in cloud environments. Traditional relational databases were designed in a different hardware\nand software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL\nand NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the\nlarge number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and\neven more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL\nand NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to\npractitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities\nin the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling,\nand security related capabilities. Features driving the ability to scale read requests and write requests, or scaling\ndata storage are investigated, in particular partitioning, replication, consistency, and concurrency control.\nFurthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and\nthe suitability of various solutions for different sets of applications is examined. Consequently, this study has\nidentified challenges in the field, including the immense diversity and inconsistency of terminologies, limited\ndocumentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages.
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