Abstract
In the era of cloud computing and huge information systems, distributed applications should manage dynamic workloads; i.e., the amount of client requests per time unit may vary frequently and servers should rapidly adapt their computing efforts to those workloads. Cloud systems provide a solid basis for this kind of applications but most of the traditional relational database systems are unprepared to scale up with this kind of distributed systems. This paper surveys different techniques being used in modern SQL, NoSQL and NewSQL systems in order to increase the scalability and adaptability in the management of persistent data.
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Pallardó-Lozoya, M.R., Esparza-Peidro, J., García-Escrivá, JR., Decker, H., Muñoz-Escoí, F.D. (2011). Scalable Data Management in Distributed Information Systems. In: Meersman, R., Dillon, T., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2011 Workshops. OTM 2011. Lecture Notes in Computer Science, vol 7046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25126-9_31
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