The Suitability of Graph Databases for Big Data Analysis: A Benchmark

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F20%3A00115477" target="_blank" >RIV/00216224:14610/20:00115477 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scitepress.org/PublicationsDetail.aspx?ID=qc6Zz7Qsgn0=&t=1" target="_blank" >https://www.scitepress.org/PublicationsDetail.aspx?ID=qc6Zz7Qsgn0=&t=1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0009350902130220" target="_blank" >10.5220/0009350902130220</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Suitability of Graph Databases for Big Data Analysis: A Benchmark

Popis výsledku v původním jazyce

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 databases and PostgreSQL as a representative of non-graph databases.

Název v anglickém jazyce

The Suitability of Graph Databases for Big Data Analysis: A Benchmark

Popis výsledku anglicky

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 databases and PostgreSQL as a representative of non-graph databases.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS

ISBN

9789897584268

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

213-220

Název nakladatele

SciTePress

Místo vydání

Neuveden

Místo konání akce

Prague

Datum konání akce

1. 1. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000615960700021