Comprehensive Performance and Scalability Assessment of Front-End Frameworks: React, Angular, and Vue.js

This paper discusses performance and scalability opportunities of the three major modern front-end frameworks, namely React, Angular, and Vue.js. In this respect, the research tries to point out the strengths and limitations of the compared frameworks in handling large-scale and complex web applications by evaluating each against different load conditions or scalability scenarios. It does this by running a set of benchmark applications that test performance indicators such as load times, speed of rendering, memory usage, and CPU usage. Additionally, it investigates scalability through load testing-emulation of increased user interactions and complexity testing, observing how each of these frameworks handles increasing application complexity. Overall, the results obtained were good, especially those for React, where the use of its virtual DOM was exploited, though some optimization may be necessary when handling more complex state changes. Angular has great performance, though it can show increased load times and higher memory usage due to the richness of features. Vue.js has competitive performance, with lower memory usage and faster render times, balancing simplicity with scalability quite well. The study concludes by giving insight on how to select the correct framework based on an application's particular needs and thought on scalability for guidance on choosing the right tool for the development job at hand.

Publication Details

Journal
Knowledge Commons (Lakehead University)
Published
2024-10-23
DOI
https://doi.org/10.17613/kbax-p340
Primary Topic
Mobile and Web Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive Performance and Scalability Assessment of Front-End Frameworks: React, Angular, and Vue.js

Knowledge Commons (Lakehead University)
Mobile and Web Applications
article

Comprehensive Performance and Scalability Assessment of Front-End Frameworks: React, Angular, and Vue.js

article en

Abstract

This paper discusses performance and scalability opportunities of the three major modern front-end frameworks, namely React, Angular, and Vue.js. In this respect, the research tries to point out the strengths and limitations of the compared frameworks in handling large-scale and complex web applications by evaluating each against different load conditions or scalability scenarios. It does this by running a set of benchmark applications that test performance indicators such as load times, speed of rendering, memory usage, and CPU usage. Additionally, it investigates scalability through load testing-emulation of increased user interactions and complexity testing, observing how each of these frameworks handles increasing application complexity. Overall, the results obtained were good, especially those for React, where the use of its virtual DOM was exploited, though some optimization may be necessary when handling more complex state changes. Angular has great performance, though it can show increased load times and higher memory usage due to the richness of features. Vue.js has competitive performance, with lower memory usage and faster render times, balancing simplicity with scalability quite well. The study concludes by giving insight on how to select the correct framework based on an application's particular needs and thought on scalability for guidance on choosing the right tool for the development job at hand.

Knowledge Commons (Lakehead University)
Decent work and economic growth
Openalex Percentile: Top 40%
Mobile and Web Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.