In this paper we will try to present a comparative study of non-relational databases and relational databases. We mainly focus our presentation on one implementation of the NoSQL database technology, namely MongoDB, and make a comparison with another implementation of relational databases, namely MySQL, and thus justifying why MongoDB is more efficient than MySQL. We will also present the advantages of using a non-relational database compared to a relational database, integrated in a forum in the field of personal and professional development. The NoSQL database used to develop the forum is MongoDB, and was chosen from a variety of nonrelational databases, thanks to some aspects that we will highlight in this article. The database integration in the framework will also be presented.
Abstract-The purpose of this paper is to present a comparative study between relational and non-relational database models in a web-based application, by executing various operations on both relational and on non-relational databases thus highlighting the results obtained during performance comparison tests. The study was based on the implementation of a web-based application for population records. For the nonrelational database, we used MongoDB and for the relational database, we used MSSQL 2014. We will also present the advantages of using a non-relational database compared to a relational database integrated in a web-based application, which needs to manipulate a big amount of data.
Most applications available nowadays are using an Object Relational Mapper (ORM) to access and save data. The additional layer that is being wrapped over the database induces a performance impact in detrimental of raw SQL queries; on the other side, the advantages of using ORMs by focusing on domain level through application development represent a premise for easier development and simpler code maintenance. In this context, this paper makes a performance comparison between three of the most used ORM technologies from the .NET family: Entity Framework Core 2.2, nHibernate 5.2.3 and Dapper 1.50.5. The main objective of the paper is to make a comparative analysis of the impact that a specific ORM has on application performance when realizing database requests. In order to perform the analysis, a specific testing architecture was designed to ensure the consistency of tests. Performance evaluation for time responses and memory usage for each technology was done using the same CRUD (Create Read Update Delete) operations on the database. The results obtained proved that the decision to use one of another is dependent of the most used type of operation. A comprehensive discussion based on results analysis is done in order to support a decision for choosing a specific ORM by the software engineers in the process of software design and development.
Abstract-Now-a-days, mobile applications implement complex functionalities that use device's core features extensively. This paper realizes a performance analysis of the most important core features used frequently in mobile application development: asynchronous multi-threaded code execution, drawing views/elements on the screen and basic network communications. While multiple mobile platforms have emerged in recent years, in this paper two well-established and popular operating systems were considered for comparison and testing: Android and iOS. Thus, two basic applications featuring the same functionality and complexity were developed to run natively on both platforms. Applications were developed by using development languages and tools recommended for each operating system. This paper aims to highlight the differences between the two operating systems by analyzing core feature performance metrics for both functionally identical mobile applications developed for each platform. Results obtained could be further used for guiding the optimization of application's development process for each considered operating system.
In the current context of emerging several types of database systems (relational and non-relational), choosing the type and database system for storing large amounts of data in today’s big data applications has become an important challenge. In this paper, we aimed to provide a comparative evaluation of two popular open-source database management systems (DBMSs): MySQL as a relational DBMS and, more recently, as a non-relational DBMS, and CouchDB as a non-relational DBMS. This comparison was based on performance evaluation of CRUD (CREATE, READ, UPDATE, DELETE) operations for different amounts of data to show how these two databases could be modeled and used in an application and highlight the differences in the response time and complexity. The main objective of the paper was to make a comparative analysis of the impact that each specific DBMS has on application performance when carrying out CRUD requests. To perform the analysis and to ensure the consistency of tests, two similar applications were developed in Java, one using MySQL and the other one using CouchDB database; these applications were further used to evaluate the time responses for each database technology on the same CRUD operations on the database. Finally, a comprehensive discussion based on the results of the analysis was performed that centered on the results obtained and several conclusions were revealed. Advantages and drawbacks for each DBMS are outlined to support a decision for choosing a specific type of DBMS that could be used in a big data application.
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