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Graph Databases

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Abstract

Graph databases are the technical implementation of graph theory, a concept that was introduced to applied mathematics about 200 years ago. Its versatile usability for various business and private applications fostered the establishment of a graph industry that markets graph databases, graph analysis tools, and graph frameworks. This article introduces the scientific foundations for graph theory and its realization in graph databases, and explains typical analysis tools and applications.

Keywords

  • Graph database
  • Networks
  • Cypher
  • Network analysis
  • Connected data
  • Data model
  • Graph storage
  • Graph theory
  • Queries
  • Algorithms
  • Graph query languages
  • Social networks

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  • DOI: 10.1007/978-3-030-78821-6_3
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Fig. 1

(© ifb SE)

Notes

  1. 1.

    For an English translation see König and Tutte, Theory of Finite and Infinite Graphs (2013).

  2. 2.

    In a directed graph, the edges connecting two different nodes have different meanings, depending on their direction. In an undirected graph, an edge connecting two nodes has a single meaning.

  3. 3.

    This refers to a weighted graph, where an edge can be weighted to qualify its weight or strength, e.g., cost, length, distance.

  4. 4.

    Example of Dijkstra algorithm: https://www.youtube.com/watch?v=UG7VmPWkJmA&feature=youtu.be&t=33.

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Correspondence to Krystyna Bajer .

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Bajer, K., Seidlitz, A., Steltgens, S., Wormuth, B. (2021). Graph Databases. In: Liermann, V., Stegmann, C. (eds) The Digital Journey of Banking and Insurance, Volume III. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-78821-6_3

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  • DOI: https://doi.org/10.1007/978-3-030-78821-6_3

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  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-030-78820-9

  • Online ISBN: 978-3-030-78821-6

  • eBook Packages: Economics and FinanceEconomics and Finance (R0)