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Historical Traversals in Native Graph Databases

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Advances in Databases and Information Systems (ADBIS 2017)

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Abstract

Since most graph data, such as data from social, citation and computer networks evolve over time, it is useful to be able to query their history. In this paper, we focus on supporting traversals of such graphs using a native graph database. We assume that we are given the history of an evolving graph as a sequence of graph snapshots representing the state of the graph at different time instances. We introduce models for storing such snapshots in the graph database and we propose algorithms for supporting various types of historical reachability and shortest path queries. Finally, we experimentally evaluate and compare the various models and algorithms using both real and synthetic datasets.

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Notes

  1. 1.

    https://neo4j.com/.

  2. 2.

    http://dblp.uni-trier.de.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Ioannina, Ioannina, Greece

    Konstantinos Semertzidis & Evaggelia Pitoura

Authors
  1. Konstantinos Semertzidis
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  2. Evaggelia Pitoura
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Corresponding author

Correspondence to Konstantinos Semertzidis .

Editor information

Editors and Affiliations

  1. Riga Technical University , Riga, Latvia

    Mārīte Kirikova

  2. Norwegian University of Science and Technology, Trondheim, Norway

    Kjetil Nørvåg

  3. University of Cyprus , Nicosia, Cyprus

    George A. Papadopoulos

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Semertzidis, K., Pitoura, E. (2017). Historical Traversals in Native Graph Databases. In: Kirikova, M., Nørvåg, K., Papadopoulos, G. (eds) Advances in Databases and Information Systems. ADBIS 2017. Lecture Notes in Computer Science(), vol 10509. Springer, Cham. https://doi.org/10.1007/978-3-319-66917-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-66917-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66916-8

  • Online ISBN: 978-3-319-66917-5

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