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Titlebook: Big Data Benchmarking; 6th International Wo Tilmann Rabl,Raghunath Nambiar,Saumyadipta Pyne Conference proceedings 2016 Springer Internatio

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Vector Fields Possessing an Integral, and data rate and size distributions, based on real observations. We also validate this benchmark on Apache Storm using synthetic streams and simulated application logic. This paper offers a unique glimpse into an . national identity infrastructure, and proposes a benchmark for “fast data” platforms to support such eGovernance applications.
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Asymptotically Autonomous Vector Fields,e produced regardless of any specific architecture and tuning. We apply this benchmark, which is available in the public domain, to three main proponents: rasdaman, SciQL, and SciDB. We present the benchmark and its design rationales, show the benchmark results, and comment on them.
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,The Poincaré-Bendixson Theorem,for different workloads. Our results show that . is well suited to achieve high availability while preserving table response times in case of a node failure. Especially for read intensive applications that require high availability, . is a good choice.
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Towards a General Array Database Benchmark: Measuring Storage Accesse produced regardless of any specific architecture and tuning. We apply this benchmark, which is available in the public domain, to three main proponents: rasdaman, SciQL, and SciDB. We present the benchmark and its design rationales, show the benchmark results, and comment on them.
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Benchmarking Fast-Data Platforms for the , Biometric DatabaseIndia. . processes streams of biometric data as residents are enrolled and updated. Besides .1 million enrollments and updates per day, up to 100 million daily biometric authentications are expected during delivery of various public services. These form critical Big Data applications, with large vol
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