On the web, data visualisation through charts and diagrams can help present data in a more readable way. This is often done through the usage of JavaScript libraries. We experimented with 5 JavaScript data visualisation libraries to determine their respective performances and how each one scaled with increased data size. Our results will hopefully provide help with the selection of said libraries. The results show a significant difference in response times between all libraries for mostdata sizes, with only a few exceptions. Different exponential growths were also identified for all libraries, and the performance often varied greatly depending on chart type. Response time is not the only variable in performance measurements. Future research could cover other aspects, like memory consumption and rendering requirements. There were also times when the libraries did not render at larger data sizes, despite showing no errors, and further investigation behind this should be done.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-21529 |
| Date | January 2022 |
| Creators | Magnusson Millqvist, Hamlet, Bolin, Niklas |
| Publisher | Högskolan i Skövde, Institutionen för informationsteknologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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