Publication | Closed Access
Benchmarking scalability and elasticity of distributed database systems
106
Citations
14
References
2014
Year
Cluster ComputingEngineeringCloud DatabaseComputer ArchitectureDatabase ScalabilityData ScienceDistributed DatabaseData IntegrationParallel ComputingData ManagementBenchmarking ScalabilityHbase ElasticityPerformance ImpactComputer ScienceScalable ComputingPerformance ScalabilityCloud ComputingParallel ProgrammingDistributed Data StoreBig Data
Distributed database system performance benchmarks are an important source of information for decision makers who must select the right technology for their data management problems. Since important decisions rely on trustworthy experimental data, it is necessary to reproduce experiments and verify the results. We reproduce performance and scalability benchmarking experiments of HBase and Cassandra that have been conducted by previous research and compare the results. The scope of our reproduced experiments is extended with a performance evaluation of Cassandra on different Amazon EC2 infrastructure configurations, and an evaluation of Cassandra and HBase elasticity by measuring scaling speed and performance impact while scaling.
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