Abstract
Collecting, transforming and analyzing data is seeing an all time high interest over the last few years. Due to the large amount of emerging or enhanced data management systems, as well as the high amount of differences in features and options they support, this paper is focused on reviewing the existing systems that are part of the NewSQL category. By looking at the top nine most used and researched implementations this work investigates how these compare in terms of supported data models, transactionality features and querying abilities. Furthermore, it provides an overview of scalability implementations and functionality as well as security assets and liabilities. It also includes an analysis of costs, by looking at both licensing as well as infrastructural support. This work can be used as a guiding analysis for providing insights into what features are supported and offered by the top NewSQL systems available over multiple dimensions.
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Acknowledgments
This research was made possible by funding from the ICT-AGRI-FOOD 2020 Joint Call. This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CCCDI - UEFISCDI, project number COFUND-ICT-AGRI-FOOD-MUSHNOMICS 205/2020, within PNCDI III.
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Chereja, I., Hahn, S.M.L., Matei, O., Avram, A. (2021). Multidimensional Analysis of NewSQL Database Systems. In: Silhavy, R. (eds) Software Engineering and Algorithms. CSOC 2021. Lecture Notes in Networks and Systems, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-030-77442-4_19
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DOI: https://doi.org/10.1007/978-3-030-77442-4_19
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