论文信息 - Experimental Comparison of Graph Databases

Experimental Comparison of Graph Databases

In the recent years a new type of NoSQL databases, called graph databases (GDBs), has gained significant popularity due to the increasing need of processing and storing data in the form of a graph. The objective of this paper is a research on possibilities and limitations of GDBs and conducting an experimental comparison of selected GDB implementations. For this purpose the requirements of a universal GDB benchmark have been formulated and an extensible benchmarking tool, called BlueBench, has been developed.

Irena Holubová | Martin Svoboda | Vojtech Kolomicenko

[1] Yixin Chen,et al. A comparison of a graph database and a relational database: a data provenance perspective , 2010, ACM SE '10.

[2] Jure Leskovec,et al. Statistical properties of community structure in large social and information networks , 2008, WWW.

[3] Josep-Lluís Larriba-Pey,et al. Survey of Graph Database Performance on the HPC Scalable Graph Analysis Benchmark , 2010, WAIM Workshops.

[4] Jim Webber,et al. Graph Databases: New Opportunities for Connected Data , 2013 .

[5] Alan M. Frieze,et al. Random graphs , 2006, SODA '06.

[6] Ladislav Hluchý,et al. Benchmarking Traversal Operations over Graph Databases , 2012, 2012 IEEE 28th International Conference on Data Engineering Workshops.

[7] Albert,et al. Emergence of scaling in random networks , 1999, Science.

[8] Christos Faloutsos,et al. R-MAT: A Recursive Model for Graph Mining , 2004, SDM.

[9] Andrea Lancichinetti,et al. Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.