Comparative analysis of the selected relational database management systems

Poljak, R.; Poščić, Patrizia; Jakšić, Danijela

doi:10.23919/mipro.2017.7973658

Cited by 10 publications

(7 citation statements)

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“…Therefore, reliable or not, these two tools are determined by the needs of a company is using it. When compared to previous research [24], [25], [26], this study uses the same method of quantitative comparative analysis. Previous research has proven that Apache Spark and Oracle Database are superior to their comparison tools.…”

Section: Resultsmentioning

confidence: 99%

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Comparison of Apache SparkSQL and Oracle Performance: Case Study of Data Cleansing Process

Hidayati

Kusumasari²,

Hamami³

2022

JOIV : Int. J. Inform. Visualization

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A dataset with good quality is a valuable asset for a company. The data can be processed into information to help companies improve decision-making. However, the data increased more and more over time to decrease data quality. Thus, good data management is important to keep data quality meeting company standards. One of the efforts that can be done is conducting data cleansing to clean data from errors, inaccuracies, duplication, format discrepancies, etc. Apache Spark is an engine that can analyze large amounts of data. Oracle Database is a database management system used to manage databases. Both have their own reliability and can be used to analyze SQL-shaped data. This study compared Spark and Oracle performance based on query processing time. Both were tested on queries used to perform data cleansing of millions of rows of the dataset. The research focuses on finding out Spark and Oracle's performance through quantitative analysis. The results of this study showed that there were differences in query processing times on both tools. Apache Spark is rated better because it has a relatively faster query processing time than Oracle Database. It can be concluded that Oracle is more reliable in storing complex data models than in analyzing large data. For future research, it is suggested to add other comparison aspects such as memory and CPU usage. The researchers can also consider using query optimization techniques to enrich query experiments.

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Section: Resultsmentioning

confidence: 99%

“…This research successfully showed that Spark has a processing time performance superior to normal and iterative queries. Next, research by Poljak et al [26] compared MySQL, Oracle, and PostgreSQL performance in multiple indicators. In the query speed performance indicator, Oracle is better than others.…”

Section: B Related Workmentioning

confidence: 99%

Comparison of Apache SparkSQL and Oracle Performance: Case Study of Data Cleansing Process

Hidayati

Kusumasari²,

Hamami³

2022

JOIV : Int. J. Inform. Visualization

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“…Oracle PL/SQL has been used in several applications that require data-intensive analysis [27][28][29]. P o l j a k, P o s c i c and J a k s i c [30] identify some of the main advantages of an Oracle database when compared to other relational databases, unleashing its robustness, reliability and performance optimization for large data volume. Oracle uses two engines to process PL/SQL code: all procedural code is handled by the PL/SQL engine; while all SQL code is handled by the SQL statement executor or SQL engine.…”

Section: Optimization Techniques In Oracle Pl/sqlmentioning

confidence: 99%

Performance Analysis and Optimization Techniques for Oracle Relational Databases

Almeida

Araújo

2019

Cybernetics and Information Technologies

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Databases provide an efficient way to store, retrieve and analyze data. Oracle relational database is one of the most popular database management systems that is widely used in a different variety of industries and businesses. Therefore, it is important to guarantee that the database access and data manipulation is optimized for reducing database system response time. This paper intends to analyze the performance and the main optimization techniques (Forall, Returning, and Bulk Collect) that can be adopted for Oracle Relational Databases. The results have shown that the adoption of Forall and Bulk Collect approaches bring significant benefits in terms of execution time. Furthermore, the growth rate of the average execution time is lower for Bulk Collect than Forall. However, adoption of Returning approach doesn’t bring significant statistical benefits.

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“…a Person's ID number). Popular models of relational databases used in web application development are MySQL and PostgreSQL [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Performance of Open Source Databases in Web Application Development

Savić,

Vučetić,

Milić

2023

SPSUNP

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One of the dilemmas faced by developers of Web application is whether to use SQL or NoSQL database with the unavoidable fact that application must have a quick response. Often these applications work with large amounts of data. This paper presents a comparative analysis of performance of open source SQL and NoSQL databases used in web application development. We tested behavior of different open source SQL and NoSQL databases by different parameters and give some conclusions about suitability of their application in different cases.

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Comparative analysis of the selected relational database management systems

Cited by 10 publications

References 0 publications

Comparison of Apache SparkSQL and Oracle Performance: Case Study of Data Cleansing Process

Comparison of Apache SparkSQL and Oracle Performance: Case Study of Data Cleansing Process

Performance Analysis and Optimization Techniques for Oracle Relational Databases

Comparative Analysis of Performance of Open Source Databases in Web Application Development

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