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A Discussion on the Design of Graph Database Benchmarks

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6417))

Abstract

Graph Database Management systems (GDBs) are gaining popularity. They are used to analyze huge graph datasets that are naturally appearing in many application areas to model interrelated data. The objective of this paper is to raise a new topic of discussion in the benchmarking community and allow practitioners having a set of basic guidelines for GDB benchmarking. We strongly believe that GDBs will become an important player in the market field of data analysis, and with that, their performance and capabilities will also become important. For this reason, we discuss those aspects that are important from our perspective, i.e. the characteristics of the graphs to be included in the benchmark, the characteristics of the queries that are important in graph analysis applications and the evaluation workbench.

The members of DAMA-UPC thank the Ministry of Science and Innovation of Spain and Generalitat de Catalunya, for grant numbers TIN2009-14560-C03-03 and GRC-1087 respectively.

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References

  1. Angles, R., Gutiérrez, C.: Survey of graph database models. ACM Comput. Surv. 40(1) (2008)

    Google Scholar 

  2. Neo4j: The neo database (2006), http://dist.neo4j.org/neo-technology-introduction.pdf

  3. HypergraphDB: HypergraphDB website, http://www.kobrix.com/hgdb.jsp (last retrieved in March 2010)

  4. Infogrid: Blog, http://infogrid.org/blog/2010/03/operations-on-a-graph-database-part-4 (last retrieved in March 2010)

  5. Martínez-Bazan, N., Muntés-Mulero, V., et al.: Dex: high-performance exploration on large graphs for information retrieval. In: CIKM, pp. 573–582 (2007)

    Google Scholar 

  6. Jena-RDF: Jena documentation, http://jena.sourceforge.net/documentation.html (last retrieved in March 2010)

  7. AllegroGraph: AllegroGraph website, http://www.franz.com/agraph/ (last retrieved in May 2010)

  8. Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF. W3C (2008), http://www.w3.org/TR/rdf-sparql-query/

  9. Gremlin website: Gremlin documentation, http://wiki.github.com/tinkerpop/gremlin/ (last retrieved in June 2010)

  10. Transaction Processing Performance Council (TPC): TPC Benchmark. TPC website, http://www.tpc.org (last retrieved in June 2010)

  11. Cattell, R., Skeen, J.: Object operations benchmark. TODS 17(1), 1–31 (1992)

    Article  Google Scholar 

  12. Carey, M., DeWitt, D., Naughton, J.: The oo7 benchmark. In: SIGMOD Conference, pp. 12–21 (1993)

    Google Scholar 

  13. Schmidt, A., Waas, F., Kersten, M., Carey, M., Manolescu, I., Busse, R.: Xmark: A benchmark for xml data management. In: VLDB, pp. 974–985 (2002)

    Google Scholar 

  14. Guo, Y., Pan, Z., Heflin, J.: Lubm: A benchmark for owl knowledge base systems. J. Web Sem. 3(2-3), 158–182 (2005)

    Article  Google Scholar 

  15. Bader, D., Feo, J., Gilbert, J., Kepner, J., Koetser, D., Loh, E., Madduri, K., Mann, B., Meuse, T., Robinson, E.: HPC Scalable Graph Analysis Benchmark v1.0. HPC Graph Analysis (February 2009)

    Google Scholar 

  16. Dominguez-Sal, D., Urbón-Bayes, P., Giménez-Vañó, A., Gómez-Villamor, S., Martínez-Bazán, N., Larriba-Pey, J.L.: Survey of graph database performance on the hpc scalable graph analysis benchmark. In: Shen, H.T., Pei, J., Özsu, M.T., Zou, L., Lu, J., Ling, T.-W., Yu, G., Zhuang, Y., Shao, J. (eds.) WAIM 2010. LNCS, vol. 6185, pp. 37–48. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  17. INSNA: International network for social network analysis, http://www.insna.org/

  18. OReilly, T.: What is Web 2.0: Design patterns and business models for the next generation of software (2005)

    Google Scholar 

  19. Abiteboul, S., Buneman, P., Suciu, D.: Data on the Web: from relations to semistructured data and XML. Morgan Kaufmann Publishers Inc., San Francisco (2000)

    Google Scholar 

  20. Brickley, D., Guha, R.V.: Resource description framework (rdf) schema specification 1.0. W3C Candidate Recommendation (2000)

    Google Scholar 

  21. Shasha, D., Wang, J., Giugno, R.: Algorithmics and applications of tree and graph searching. In: PODS, pp. 39–52. ACM, New York (2002)

    Google Scholar 

  22. Anyanwu, K., Sheth, A.: ρ-queries: Enabling querying for semantic associations on the semantic web. In: WWW, pp. 690–699. ACM Press, New York (2003)

    Google Scholar 

  23. Chakrabarti, D., Faloutsos, C.: Graph mining: Laws, generators, and algorithms. ACM Computing Surveys (CSUR) 38(1), 2 (2006)

    Article  Google Scholar 

  24. BioGRID: General repository for interaction datasets, http://www.thebiogrid.org/

  25. PDB: Rcsb protein data bank, http://www.rcsb.org/

  26. NAViGaTOR, http://ophid.utoronto.ca/navigator/

  27. Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems 30(1-7), 107–117 (1998)

    Article  Google Scholar 

  28. Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46(5), 604–632 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  29. Strands: e-commerce recommendation engine, http://recommender.strands.com/

  30. Chein, M., Mugnier, M.: Conceptual graphs: fundamental notions. Revue d’Intelligence Artificielle 6, 365–406 (1992)

    Google Scholar 

  31. DirectedEdge: a recommendation engine, http://www.directededge.com (last retrieved in June 2010)

  32. Amadeus: Global travel distribution system, http://www.amadeus.net/

  33. Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: CHI, pp. 1361–1370 (2010)

    Google Scholar 

  34. Goertzel, B.: OpenCog Prime: Design for a Thinking Machine. Online wikibook (2008), http://opencog.org/wiki/OpenCogPrime

  35. Erdos, P., Renyi, A.: On random graphs. Mathematicae 6(290-297), 156 (1959)

    MATH  Google Scholar 

  36. Leskovec, J., Lang, L., Dasgupta, A., Mahoney, M.: Statistical properties of community structure in large social and information networks. In: WWW, pp. 695–704 (2008)

    Google Scholar 

  37. Flickr: Four Billion, http://blog.flickr.net/en/2009/10/12/4000000000/ (last retrieved in June 2010)

  38. Faloutsos, M., Faloutsos, P., Faloutsos, C.: On power-law relationships of the internet topology. In: SIGCOMM, pp. 251–262 (1999)

    Google Scholar 

  39. McGlohon, M., Akoglu, L., Faloutsos, C.: Weighted graphs and disconnected components: patterns and a generator. In: KDD, pp. 524–532 (2008)

    Google Scholar 

  40. Bader, D., Madduri, K.: Parallel algorithms for evaluating centrality indices in real-world networks. In: ICPP, pp. 539–550 (2006)

    Google Scholar 

  41. Bitton, D., DeWitt, D., Turbyfill, C.: Benchmarking database systems a systematic approach. In: VLDB, pp. 8–19 (1983)

    Google Scholar 

  42. Transaction Processing Performance Council (TPC): TPC Benchmark H (2.11). TPC website, http://www.tpc.org/tpch/ (last retrieved in June 2010)

  43. Leskovec, J., Chakrabarti, D., Kleinberg, J., Faloutsos, C., Ghahramani, Z.: Kronecker graphs: An approach to modeling networks. Journal of Machine Learning Research 11, 985–1042 (2010)

    MathSciNet  MATH  Google Scholar 

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Dominguez-Sal, D., Martinez-Bazan, N., Muntes-Mulero, V., Baleta, P., Larriba-Pey, J.L. (2011). A Discussion on the Design of Graph Database Benchmarks. In: Nambiar, R., Poess, M. (eds) Performance Evaluation, Measurement and Characterization of Complex Systems. TPCTC 2010. Lecture Notes in Computer Science, vol 6417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18206-8_3

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  • DOI: https://doi.org/10.1007/978-3-642-18206-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18205-1

  • Online ISBN: 978-3-642-18206-8

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