Synopsis
Graph databases have become an indispensable tool for the analysis of linked data and interrelated data. As with any graph data representation, the need for using graph database systems emerge when they increase in size and complexity. Affiliated to those needs, graph database benchmarks emerge to assess the performance of such systems in application scenarios, representative of use cases. I proposed graph database benchmarks based on the idea of social network application. The benchmark implements and proposes a data generator that synthetically generate graphs. Also a set of high level application queries on this application that model parts of the behavior of social network users. I also studied the graph database benchmarks results that affects the performance of graph database systems. I proposed graph database benchmarks in terms of data model, query workload, large datasets and usage scenarios. I discussed the characteristics of Neo4j and DEX graph databases to be included in the benchmarks. Also I studied, the characteristics of these graph databases queries that are important in the application of graph analysis.
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About the Author
Rahul Arun.Deshmukh,Msc in Research in Computer and System Engineering, Technische University Ilmenau, Germany.
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Benchmarking In Graph Databases
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LAP LAMBERT Academic Publishing Feb 2014, 2014
ISBN 10: 3659112739
ISBN 13: 9783659112737
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Graph databases have become an indispensable tool for the analysis of linked data and interrelated data. As with any graph data representation, the need for using graph database systems emerge when they increase in size and complexity. Affiliated to those needs, graph database benchmarks emerge to assess the performance of such systems in application scenarios, representative of use cases. I proposed graph database benchmarks based on the idea of social network application. The benchmark implements and proposes a data generator that synthetically generate graphs. Also a set of high level application queries on this application that model parts of the behavior of social network users. I also studied the graph database benchmarks results that affects the performance of graph database systems. I proposed graph database benchmarks in terms of data model, query workload, large datasets and usage scenarios. I discussed the characteristics of Neo4j and DEX graph databases to be included in the benchmarks. Also I studied, the characteristics of these graph databases queries that are important in the application of graph analysis. 84 pp. Englisch. Seller Inventory # 9783659112737
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Benchmarking in Graph Databases
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Benchmarking in Graph Databases
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Benchmarking In Graph Databases
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Deshmukh RahulRahul Arun.Deshmukh,Msc in Research in Computer and System Engineering, Technische University Ilmenau, Germany.Graph databases have become an indispensable tool for the analysis of linked data and interrelated data. Seller Inventory # 5132208
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Benchmarking In Graph Databases
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LAP LAMBERT Academic Publishing Feb 2014, 2014
ISBN 10: 3659112739
ISBN 13: 9783659112737
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Graph databases have become an indispensable tool for the analysis of linked data and interrelated data. As with any graph data representation, the need for using graph database systems emerge when they increase in size and complexity. Affiliated to those needs, graph database benchmarks emerge to assess the performance of such systems in application scenarios, representative of use cases. I proposed graph database benchmarks based on the idea of social network application. The benchmark implements and proposes a data generator that synthetically generate graphs. Also a set of high level application queries on this application that model parts of the behavior of social network users. I also studied the graph database benchmarks results that affects the performance of graph database systems. I proposed graph database benchmarks in terms of data model, query workload, large datasets and usage scenarios. I discussed the characteristics of Neo4j and DEX graph databases to be included in the benchmarks. Also I studied, the characteristics of these graph databases queries that are important in the application of graph analysis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch. Seller Inventory # 9783659112737
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Benchmarking In Graph Databases
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ISBN 10: 3659112739
ISBN 13: 9783659112737
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Graph databases have become an indispensable tool for the analysis of linked data and interrelated data. As with any graph data representation, the need for using graph database systems emerge when they increase in size and complexity. Affiliated to those needs, graph database benchmarks emerge to assess the performance of such systems in application scenarios, representative of use cases. I proposed graph database benchmarks based on the idea of social network application. The benchmark implements and proposes a data generator that synthetically generate graphs. Also a set of high level application queries on this application that model parts of the behavior of social network users. I also studied the graph database benchmarks results that affects the performance of graph database systems. I proposed graph database benchmarks in terms of data model, query workload, large datasets and usage scenarios. I discussed the characteristics of Neo4j and DEX graph databases to be included in the benchmarks. Also I studied, the characteristics of these graph databases queries that are important in the application of graph analysis. Seller Inventory # 9783659112737