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Compact and efficient representation of general graph databases

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Abstract

In this paper, we propose a compact data structure to store labeled attributed graphs based on the \(k^2\)-tree, which is a very compact data structure designed to represent a simple directed graph. The idea we propose can be seen as an extension of the \(k^2\)-tree to support property graphs. In addition to the static approach, we also propose a dynamic version of the storage representation, which allows flexible schemas and insertion or deletion of data. We provide an implementation of a basic set of operations, which can be combined to form complex queries over these graphs with attributes. We evaluate the performance of our proposal with existing graph database systems and prove that our compact attributed graph representation obtains also competitive time results.

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Notes

  1. http://sparsity-technologies.com/.

  2. http://neo4j.org/.

  3. http://hypergraphdb.org/.

  4. https://www.sap.com/products/hana.html.

  5. http://www.orientechnologies.com/orientdb/.

  6. http://thinkaurelius.github.io/titan/.

  7. http://giraph.apache.org/.

  8. rank(B, i) computes the number of ones that are set up in bitmap B until position i.

  9. select(B, i) obtains the position in B of the i-th 1.

  10. A wavelet tree is a data structure that maintains a sequence S of n symbols supporting the following operations: access(S, i), which returns the symbol at position i in S; \(rank_c(S, i)\), which counts the times symbol c appears up to position i in S; and \(select_c(S, j)\), which returns the position in S of the j-th appearance of symbol c. They can be efficiently implemented using compressed space and perform well in practice. Wavelet trees and their applications have been extensively described by [31].

  11. https://github.com/xxsds/DYNAMIC.

  12. http://movielens.umn.edu/.

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Acknowledgements

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie [Grant Agreement No 690941]; from the Ministerio de Economía y Competitividad (PGE and ERDF) [Grant Numbers TIN2015-69951-R; TIN2016-77158-C4-3-R] and from Xunta de Galicia (co-founded with ERDF) [Grant Numbers ED431C 2017/58; ED431G/01]. We also thank Nieves R. Brisaboa for her contributions during the initial discussions of this work.

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Authors and Affiliations

  1. Indra, A Coruña, Spain

    Sandra Álvarez-García

  2. Enxenio S.L., A Coruña, Spain

    Borja Freire

  3. CITIC, Database Laboratory, Universidade da Coruña, Campus de Elviña, 15071, A Coruña, Spain

    Susana Ladra & Óscar Pedreira

Authors
  1. Sandra Álvarez-García
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  2. Borja Freire
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  3. Susana Ladra
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  4. Óscar Pedreira
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Corresponding author

Correspondence to Susana Ladra.

Additional information

A preliminary partial version of this paper appeared in Proceedings of the Eighth Workshop on Mining and Learning with Graphs (MLG2010), pp. 18–25, 2010.

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Álvarez-García, S., Freire, B., Ladra, S. et al. Compact and efficient representation of general graph databases. Knowl Inf Syst 60, 1479–1510 (2019). https://doi.org/10.1007/s10115-018-1275-x

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