Concurrent Access Performance Comparison Between Relational Databases and Graph NoSQL Databases for Complex Algorithms

Databases are a fundamental element of contemporary software applications. The most widely used and recognized type in practice is the relational database, valued for its ability to store and organize data in tabular structures, its emphasis on data consistency and integrity, and its use of a standa...

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Vydané v:Applied sciences Ročník 14; číslo 21; s. 9867
Hlavní autori: Lupu, Elena, Olteanu, Adriana, Ionita, Anca Daniela
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.11.2024
Predmet:
Algorithms
Analysis
Architecture
Business metrics
complex queries
Data base management systems
Efficiency
graph database
Information management
Literature reviews
Navigation systems
Neo4j
Queries
Relational data bases
relational database
Servers
Social networks
Software
SQL Server
Technology application
Workloads
ISSN:2076-3417, 2076-3417
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Abstract Databases are a fundamental element of contemporary software applications. The most widely used and recognized type in practice is the relational database, valued for its ability to store and organize data in tabular structures, its emphasis on data consistency and integrity, and its use of a standardized query language, SQL. However, with the rapid increase in both the volume and complexity of data, relational databases have recently encountered challenges in effectively modeling this expanding information. To address performance challenges, new database systems have emerged, offering alternative approaches to data modeling—these are known as NoSQL databases. In this paper, we present an indoor navigation application designed to operate on both a relational database, Microsoft SQL Server, and a graph-based NoSQL database, Neo4j. We describe the algorithms implemented for testing and the performance metrics analyzed to draw our conclusions. The results revealed Neo4j’s strength in managing data with complex relationships but also exposed its limitations in handling concurrent access, where SQL Server demonstrated significantly greater stability.
AbstractList Databases are a fundamental element of contemporary software applications. The most widely used and recognized type in practice is the relational database, valued for its ability to store and organize data in tabular structures, its emphasis on data consistency and integrity, and its use of a standardized query language, SQL. However, with the rapid increase in both the volume and complexity of data, relational databases have recently encountered challenges in effectively modeling this expanding information. To address performance challenges, new database systems have emerged, offering alternative approaches to data modeling—these are known as NoSQL databases. In this paper, we present an indoor navigation application designed to operate on both a relational database, Microsoft SQL Server, and a graph-based NoSQL database, Neo4j. We describe the algorithms implemented for testing and the performance metrics analyzed to draw our conclusions. The results revealed Neo4j’s strength in managing data with complex relationships but also exposed its limitations in handling concurrent access, where SQL Server demonstrated significantly greater stability.
Audience Academic
Author Olteanu, Adriana
Lupu, Elena
Ionita, Anca Daniela
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10.3390/app12136490
10.1109/ITNEC.2019.8729264
10.3390/app10238524
10.1145/1322432.1322433
10.3390/bdcc7020097
10.3390/s22124515
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2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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SubjectTerms Algorithms
Analysis
Architecture
Business metrics
complex queries
Data base management systems
Efficiency
graph database
Information management
Literature reviews
Navigation systems
Neo4j
Queries
Relational data bases
relational database
Servers
Social networks
Software
SQL Server
Technology application
Workloads
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