Publication | Closed Access
Is elasticity of scalable databases a Myth?
13
Citations
11
References
2016
Year
Unknown Venue
Cluster ComputingEngineeringCloud DatabaseDatabasesElasticity FeaturesDatabase ScalabilityDatabase SystemsScalable DatabasesReal-time DatabasesData ScienceManagementNosql DatabaseData IntegrationNosql DatabasesData ManagementInformation ManagementPerformance ScalabilityTechnologyEdge ComputingCloud ComputingDistributed Data StoreBig Data
The age of cloud computing has introduced all the mechanisms needed to elastically scale distributed, cloud-enabled applications. At roughly the same time, NoSQL databases have been proclaimed as the scalable alternative to relational databases. Since then, NoSQL databases are a core component of many large-scale distributed applications. This paper evaluates the scalability and elasticity features of the three widely used NoSQL database systems Couchbase, Cassandra and MongoDB under various workloads and settings using throughput and latency as metrics. The numbers show that the three database systems have dramatically different baselines with respect to both metrics and also behave unexpected when scaling out. For instance, while Couchbase's throughput increases by 17% when scaled out from 1 to 4 nodes, MongoDB's throughput decreases by more than 50%. These surprising results show that not all tested NoSQL databases do scale as expected and even worse, in some cases scaling harms performances.
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