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Authors: Jaroslav Pokorný 1 ; Michal Valenta 2 and Martin Troup 2

Affiliations: 1 Faculty of Mathematics and Physics, Charles University, Prague and Czech Republic ; 2 Faculty of Information Technology, Czech Technical University, Prague and Czech Republic

ISBN: 978-989-758-318-6

Keyword(s): Graph Databases, Indexing Patterns, Graph Pattern, Graph Database Schema, Neo4j.

Related Ontology Subjects/Areas/Topics: Data Engineering ; Database Architecture and Performance ; Databases and Data Security ; Nosql Databases

Abstract: Nowadays graphs have become very popular in domains like social media analytics, healthcare, natural sciences, BI, networking, graph-based bibliographic IR, etc. Graph databases (GDB) allow simple and rapid retrieval of complex graph structures that are difficult to model in traditional IS based on a relational DBMS. GDB are designed to exploit relationships in data, which means they can uncover patterns difficult to detect using traditional methods. We introduce a new method for indexing graph patterns within a GDB modelled as a labelled property graph. The index is organized in a tree structure and stored in the same database where the database graph. The method is analysed and implemented for Neo4j GDB engine. It enables to create, use and update indexes that are used to speed-up the process of matching graph patterns. The paper provides a comparison between queries with and without using indexes.

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Paper citation in several formats:
Pokorný, J.; Valenta, M. and Troup, M. (2018). Indexing Patterns in Graph Databases.In Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-318-6, pages 313-321. DOI: 10.5220/0006826903130321

@conference{data18,
author={Jaroslav Pokorný. and Michal Valenta. and Martin Troup.},
title={Indexing Patterns in Graph Databases},
booktitle={Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2018},
pages={313-321},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006826903130321},
isbn={978-989-758-318-6},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Indexing Patterns in Graph Databases
SN - 978-989-758-318-6
AU - Pokorný, J.
AU - Valenta, M.
AU - Troup, M.
PY - 2018
SP - 313
EP - 321
DO - 10.5220/0006826903130321

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