Enhancing Angular Applications with Server-Side Rendering (SSR)

Authors

  • Nikhil Kodali

Keywords:

Server-Side Rendering (SSR), Angular Universal, SEO Optimization, Hydration Process, Lazy Loading.

Abstract

This paper delves into the, Server-Side Rendering (SSR) in Angular has become a pivotal technique for enhancing web application performance. By rendering pages on the server instead of the client browser, SSR results in faster initial page load times, improved SEO optimization, and better accessibility. Angular's Universal framework equips developers with the tools necessary to implement SSR, allowing for pre-rendering of HTML content before it reaches the client. Recent advancements include streamlined hydration processes, simplified SSR integration, and enhanced support for modern web features like lazy loading and caching. This paper explores these developments and their impact on optimizing performance, user experience, and search engine rankings for Angular applications.

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References

Akbar, Andi M. Ali Mahdi, et al. "Fast and Efficient Cluster Based Map for Ship Tracking." 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia. IEEE, 2018.

Bivand, R. (2022), "R Packages for Analyzing Spatial Data: A Comparative Case Study with Areal Data." Geogr Anal, 54: 488-518. https://doi.org/10.1111/gean.12319

Breunig, M., Bradley, P.E., Jahn, M., Kuper, P., Mazroob, N., Rösch, N., Al-Doori, M., Stefanakis, E., Jadidi, M. "Geospatial Data Management Research: Progress and Future Directions." ISPRS Int. J. Geo-Inf. 2020, 9, 95. https://doi.org/10.3390/ijgi9020095

da Costa Rainho, Filipe, Jorge Bernardino. "Web GIS: A new system to store spatial data using GeoJSON in MongoDB." 2018 13th Iberian Conference on Information Systems and Technologies. IEEE, 2018.

E. Baralis, A. Dalla Valle, P. Garza, C. Rossi, and F. Scullino, "SQL versus NoSQL databases for geospatial applications," 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, USA, 2017, pp. 3388-3397, https://doi.org/10.1109/BigData.2017.8258324.

Guo, D., Onstein, E. "State-of-the-Art Geospatial Information Processing in NoSQL Databases." ISPRS Int. J. Geo-Inf. 2020, 9, 331. https://doi.org/10.3390/ijgi9050331

Murray, S. "Interactive Data Visualization for the Web: An Introduction to Designing with D3." O'Reilly Media, 2017.

Netek, R., Brus, J., Tomecka, O. "Performance Testing on Marker Clustering and Heatmap Visualization Techniques: A Comparative Study on JavaScript Mapping Libraries." ISPRS Int. J. Geo-Inf. 2019, 8, 348. https://doi.org/10.3390/ijgi8080348

Nikparvar, B., Thill, J.-C. "Machine Learning of Spatial Data." ISPRS Int. J. Geo-Inf. 2021, 10, 600. https://doi.org/10.3390/ijgi10090600

Richter, A., Löwner, M.-O., Ebendt, R., Scholz, M. "Towards an integrated urban development considering novel intelligent transportation systems: Urban Development Considering Novel Transport." Technological Forecasting and Social Change, Volume 155, 119970, ISSN 0040-1625, 2020.

Shah, Purnima, and Sanjay Chaudhary. "Big data analytics framework for spatial data." Big Data Analytics: 6th International Conference, BDA 2018, Warangal, India, December 18–21, 2018, Proceedings 6. Springer International Publishing, 2018.

Vasavi, S., Padma Priya, M., Anu A. Gokhale. "Framework for geospatial query processing by integrating cassandra with hadoop." Knowledge Computing and Its Applications: Knowledge Manipulation and Processing Techniques: Volume 1 (2018): 131-160.

Zhang, W., Gu, X., Tang, L., Yin, Y., Liu, D., Zhang, Y. "Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge." Gondwana Research, Volume 109, Pages 1-17, ISSN 1342-937X, 2022. https://doi.org/10.1016/j.gr.2022.03.015.

Zhou, C., Lu, H., Xiang, Y., Wu, J., Wang, F. "GeohashTile: Vector Geographic Data Display Method Based on Geohash." ISPRS Int. J. Geo-Inf. 2020, 9, 418. https://doi.org/10.3390/ijgi9070418.

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Published

16.07.2023

How to Cite

Nikhil Kodali. (2023). Enhancing Angular Applications with Server-Side Rendering (SSR). International Journal of Intelligent Systems and Applications in Engineering, 11(3), 1270 –. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/7033

Issue

Section

Research Article