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WGB: Towards a Universal Graph Benchmark

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Advancing Big Data Benchmarks (WBDB 2013, WBDB 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8585))

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Abstract

Graph data are of growing importance in many recent applications. There are many systems proposed in the last decade for graph processing and analysis. Unfortunately, with the exception of RDF stores, every system uses different datasets and queries to assess its scalability and efficiency. This makes it challenging (and sometimes impossible) to conduct a meaningful comparison. Our aim is to close this gap by introducing Waterloo Graph Benchmark (WGB), a benchmark for graph processing systems that offers an efficient generator that creates dynamic graphs with properties similar to real-life ones. WGB includes the basic graph queries which are used for building graph applications.

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Notes

  1. 1.

    http://snap.stanford.edu/data/

  2. 2.

    www.graphanalysis.org/index.html

  3. 3.

    http://www.orientdb.org/

  4. 4.

    http://www.sparsity-technologies.com/dex

  5. 5.

    http://www.neo4j.org

  6. 6.

    http://www.graph500.org/ (accessed on 24th May 2013)

  7. 7.

    http://parlab.eecs.berkeley.edu/wiki/media/patterns/map-reduce-pattern.doc

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Acknowledgments

This research was partially supported by a fellowship from IBM Centre for Advanced Studies (CAS), Toronto.

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Authors and Affiliations

  1. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada

    Khaled Ammar & M. Tamer Özsu

Authors
  1. Khaled Ammar
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  2. M. Tamer Özsu
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Corresponding author

Correspondence to Khaled Ammar .

Editor information

Editors and Affiliations

  1. University of Toronto, Toronto, Ontario, Canada

    Tilmann Rabl

  2. Cisco Systems, Inc., San José, USA

    Nambiar Raghunath

  3. Oracle Corporation, Redwood Shores, USA

    Meikel Poess

  4. Pivotal Software, Inc., Palo Alto, USA

    Milind Bhandarkar

  5. University of Toronto, Toronto, Canada

    Hans-Arno Jacobsen

  6. University of California at San Diego, La Jolla, USA

    Chaitanya Baru

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Ammar, K., Özsu, M.T. (2014). WGB: Towards a Universal Graph Benchmark. In: Rabl, T., Raghunath, N., Poess, M., Bhandarkar, M., Jacobsen, HA., Baru, C. (eds) Advancing Big Data Benchmarks. WBDB WBDB 2013 2013. Lecture Notes in Computer Science(), vol 8585. Springer, Cham. https://doi.org/10.1007/978-3-319-10596-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-10596-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10595-6

  • Online ISBN: 978-3-319-10596-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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