Comparative analysis of frameworks and automation tools in terms of functionality and performance on the Salesforce CRM Platform
Abstract
Article describes comparative analysis of both code and low-code automation tools together with frameworks used for developing graphical user interfaces that are available on the Salesforce Platform. The research is being carried out due to lack of such comparison in the available literature and due to popularity of the Salesforce CRM. Four automation tools were put together: code-based Apex Triggers and three point-and-click tools: Workflow Rules, Process Builder, Flow Builder. In each of the frameworks (Visualforce, Aura Components, Lightning Web Components) an application module was developed and example logic was implemented in each of the automation tools. DML operations insert, update, delete were compared in terms of performance and each technology was analyzed in terms of provided functionalities and limitations. It was concluded that the most efficient automation tool is Flow Builder and the Lightning Web Components framework is the best choice for developing graphical user interfaces.
Keywords:
Salesforce, performance, low-code tools, frameworksReferences
R. Waszkowski, Low-code platform for automating business processes in manufacturing, IFAC-PapersOnLine 52(10) (2019) 376–381, https://doi.org/10.1016/j.ifacol.2019.10.060.
DOI: https://doi.org/10.1016/j.ifacol.2019.10.060
Google Scholar
N. Carroll, L. Móráin, D. Garrett, A. Jamnadass, The importance of citizen development for digital transformation, Cutter IT Journal 34(3) (2021) 5–9.
Google Scholar
J. Wong, M. Driver, P. Vincent, Low-code development technologies evaluation guide, Gartner, 2019.
Google Scholar
Gartner Forecasts Worldwide Low-Code Development Technologies Market to Grow 20% in 2023, https://www.gartner.com/en/newsroom/press-releases/2022-12-13-gartner-forecasts-worldwide-low-code-development-technologies-market-to-grow-20-percent-in-2023, [06.03.2023].
Google Scholar
Salesforce ranked #1 CRM Provider for Ninth Consecutive Year, https://www.salesforce.com/news/stories/salesforce-ranked-1-crm-provider-for-ninth-consecutive-year/, [21.01.2023].
Google Scholar
Lightning Web Components, https://lwc.dev/, [07.02.2023].
Google Scholar
H. Thanduparakkal, P. Shahad, C. G. Raji, Using Salesforce to Build Real Time Covid 19 Tracker with Cloud Computing Technology, Proceedings of the International Conference on Applied Artificial Intelligence and Computing, ICAAIC, Salem, India (2022) 942–948, https://doi.org/10.1109/ICAAIC53929.2022.9792802.
DOI: https://doi.org/10.1109/ICAAIC53929.2022.9792802
Google Scholar
V. Sharma, S. Saraswat, S. Verma, P. Banga, D. Gupta, Cost-Effective Data Mining Application Covid-19 Analyzer, Proceedings of the 5th International Conference on Information Systems and Computer Networks, ISCON, Mathura, India (2021) 1–5, https://doi.org/10.1109/ISCON52037.2021.9702328.
DOI: https://doi.org/10.1109/ISCON52037.2021.9702328
Google Scholar
A. Poniszewska-Maranda, R. Matusiak, N. Kryvinska, Use of Salesforce platform for building real-time service systems in cloud, Proceedings of the IEEE International Conference on Services Computing, SCC, Honolulu, HI, USA (2017) 491–494, https://doi.org/10.1109/SCC.2017.72.
DOI: https://doi.org/10.1109/SCC.2017.72
Google Scholar
R. Gupta, S. Verma, K. Janjua, Custom application development in cloud environment: Using salesforce, Proceedings of the 4th International Conference on Computing Sciences, ICCS, Jalandhar, India (2018) 23–27, https://doi.org/10.1109/ICCS.2018.00010.
DOI: https://doi.org/10.1109/ICCS.2018.00010
Google Scholar
D. R. Miącz, Analiza wydajności metod tworzenia aplikacji w technologii Salesforce, Journal of Computer Sciences Institute 10 (2019) 24–27, https://doi.org/10.35784/jcsi.189.
DOI: https://doi.org/10.35784/jcsi.189
Google Scholar
W. Marańda, A. Poniszewska-Marańda, M. Szymczyńska, Data Processing in Cloud Computing Model on the Example of Salesforce Cloud, Information 13(2) (2022) 85, https://doi.org/10.3390/info13020085.
DOI: https://doi.org/10.3390/info13020085
Google Scholar
D. Appleman, R. Watson, The Dark Art Of CPU Benchmarking, https://www.salesforce.com/video/296515/, [16.02.2023].
Google Scholar
Statistics
Abstract views: 289PDF downloads: 315
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.