2015 · 12 citations · 10 references
ComputingComputer SystemsBig Data AnalyticsData AnalyticsData ManagementData WarehousingPerformance Bottleneck AnalysisApplication-level PerformanceBig Data Analytics ArchitectureBig Data ArchitectureCustomer Requirements GatheringCustomer Requirements ManagementLarge-scale Data Processing
Data is one of the most important resources for modern enterprises. Better analytics allow for a better understanding of customer requirements and market dynamics. The more data is collected, the more information can be extracted. However, information value extraction is limited by data processing speeds. Due to fast technological advances in big data management there is an abundance of big data systems. This leaves users in the dilemma of choosing a system that features good end-to-end performance for the use case. To get a good understanding of the actual performance of a system, realistic application level workloads are required.
10
Benchmarking cloud serving systems with YCSB
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Evaluation campaigns and TRECVid
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Computing, Computer Science, Physics +11
Stream Bench: Towards Benchmarking Modern Distributed Stream Computing Frameworks