How well a multi-model database performs against its single-model variants: Benchmarking OrientDB with Neo4j and MongoDB

MACÁK, Martin, Matúš ŠTOVČIK, Barbora BÜHNOVÁ and Michal MERJAVÝ. How well a multi-model database performs against its single-model variants: Benchmarking OrientDB with Neo4j and MongoDB. In Proceedings of the 2020 Federated Conference on Computer Science and Information Systems. New York: IEEE. p. 463-470. ISBN 978-83-955416-7-4. doi:10.15439/2020F76. 2020.

Basic information

• Original name: How well a multi-model database performs against its single-model variants: Benchmarking OrientDB with Neo4j and MongoDB
• Authors: MACÁK, Martin (703 Slovakia, belonging to the institution), Matúš ŠTOVČIK (703 Slovakia, belonging to the institution), Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution) and Michal MERJAVÝ (703 Slovakia, belonging to the institution).
• Edition: New York, Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, p. 463-470, 8 pp. 2020.
• Publisher: IEEE

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• WWW: URL
• RIV identification code: RIV/00216224:14610/20:00116187
• Organization unit: Institute of Computer Science
• ISBN: 978-83-955416-7-4
• ISSN: 2300-5963
• Doi: http://dx.doi.org/10.15439/2020F76
• Keywords in English: Big Data; Benchmark; Multi-model Database; OrientDB; Neo4j; MongoDB
• Tags: firank_B, rivok
• Tags: International impact, Reviewed

Abstract

Digitalization is currently the key factor for progress, with a rising need for storing, collecting, and processing large amounts of data. In this context, NoSQL databases have become a popular storage solution, each specialized on a specific type of data. Next to that, the multi-model approach is designed to combine benefits from different types of databases, supporting several models for data. Despite its versatility, a multi-model database might not always be the best option, due to the risk of worse performance comparing to the single-model variants. It is hence crucial for software engineers to have access to benchmarks comparing the performance of multi-model and single-model variants. Moreover, in the current Big Data era, it is important to have cluster infrastructure considered within the benchmarks. In this paper, we aim to examine how the multi-model approach performs compared to its single-model variants. To this end, we compare the OrientDB multi-model database with the Neo4j graph database and the MongoDB document store. We do so in the cluster setup, to enhance state of the art in database benchmarks, which is not yet giving much insight into cluster-operating database performance.

Links

• EF16_013/0001802, research and development project: Name: CERIT Scientific Cloud
• LM2015085, research and development project: Name: CERIT Scientific Cloud (Acronym: CERIT-SC)

Investor: Ministry of Education, Youth and Sports of the CR, CERIT Scientific Cloud

• MUNI/A/1411/2019, interní kód MU: Name: Aplikovaný výzkum: softwarové architektury kritických infrastruktur, bezpečnost počítačových systémů, zpracování přirozeného jazyka a jazykové inženýrství, vizualizaci velkých dat a rozšířená realita.

Investor: Masaryk University, Category A