METRICS FOR DYNAMIC SCALING OF DATABASE IN CLOUDS
https://doi.org/10.21686/2500-3925-2013-6-25-31
Abstract
This article analyzes the main methods of scaling databases (replication, sharding) and their support at the popular relational databases and NoSQL solutions with different data models: a document-oriented, key-value, column-oriented, graph. The article provides an assessment of the capabilities of modern cloud-based solution and gives a model for the organization of dynamic scaling in the cloud infrastructure. In the article are analyzed different types of metrics and are included the basic metrics that characterize the functioning parameters and database technology, as well as sets the goals of the integral metrics, necessary for the implementation of adaptive algorithms for dynamic scaling databases in the cloud infrastructure. This article was prepared with the support of RFBR grant № 13-07-00749.
About the Authors
Alexander V. Boichenko
Moscow State University of Economics, Statistics and Informatics (MESI)
Russian Federation
Russian Federation
Dmitry K. Rogojin
Moscow State University of Economics, Statistics and Informatics (MESI)
Russian Federation
Russian Federation
Dmitry G. Korneev
Moscow State University of Economics, Statistics and Informatics (MESI)
Russian Federation
Russian Federation
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Review
For citations:
Boichenko A.V., Rogojin D.K., Korneev D.G. METRICS FOR DYNAMIC SCALING OF DATABASE IN CLOUDS. Statistics and Economics. 2013;(6):189-195. (In Russ.) https://doi.org/10.21686/2500-3925-2013-6-25-31
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