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Authors: Martin Macak ; Matus Stovcik and Barbora Buhnova

Affiliation: Institute of Computer Science, Masaryk University, Brno, Czech Republic, Faculty of Informatics, Masaryk University, Brno, Czech Republic

ISBN: 978-989-758-426-8

Keyword(s): Big Data, Benchmark, Graph Database, Neo4j, PostgreSQL.

Abstract: Digitalization of our society brings various new digital ecosystems (e.g., Smart Cities, Smart Buildings, Smart Mobility), which rely on the collection, storage, and processing of Big Data. One of the recently popular advancements in Big Data storage and processing are the graph databases. A graph database is specialized to handle highly connected data, which can be, for instance, found in the cross-domain setting where various levels of data interconnection take place. Existing works suggest that for data with many relationships, the graph databases perform better than non-graph databases. However, it is not clear where are the borders for specific query types, for which it is still efficient to use a graph database. In this paper, we design and perform tests that examine these borders. We perform the tests in a cluster of three machines so that we explore the database behavior in Big Data scenarios concerning the query. We specifically work with Neo4j as a representative of graph da tabases and PostgreSQL as a representative of non-graph databases. (More)

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Paper citation in several formats:
Macak, M.; Stovcik, M. and Buhnova, B. (2020). The Suitability of Graph Databases for Big Data Analysis: A Benchmark.In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-426-8, pages 213-220. DOI: 10.5220/0009350902130220

@conference{iotbds20,
author={Martin Macak. and Matus Stovcik. and Barbora Buhnova.},
title={The Suitability of Graph Databases for Big Data Analysis: A Benchmark},
booktitle={Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2020},
pages={213-220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009350902130220},
isbn={978-989-758-426-8},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - The Suitability of Graph Databases for Big Data Analysis: A Benchmark
SN - 978-989-758-426-8
AU - Macak, M.
AU - Stovcik, M.
AU - Buhnova, B.
PY - 2020
SP - 213
EP - 220
DO - 10.5220/0009350902130220

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