A ranking out of 10 on different criteria is made between 3 major dashboarding tools from personal experience.
Speed : In terms of speed in loading data R has a edge because it isn't a cloud service like Tableau and Vega can access a JSON from any endpoint and that seems to be the best option here.
Verdict : Vega
Maintenance : Being open-source and constantly evolving, R programs often require regular checks, especially when packages dependent on your analysis are updated or rendered outdated with an R update.
Verdict : Vega and Tableau
Data Sources : Tableau is a clear winner because of the sheer variety of databases it can access. R fails to handle huge streams of data (any language that depends on internal ram of server). Vega has no hope to compete
Verdict : Tableau
Automation : It's pretty easy to automate R with a process or batch file but it's not possible in other two cases.
Verdict : RShiny
Traffic : The free version of RShiny permits only 20 active users at a time;but no such restriction with Tableau and Vega has no hosting facility
Verdict : Tableau
Advanced Analytics : With R's incredible potential to perform predictions and forecasting, it is THE tool for advanced analytics and "data science", only rivaled by Python
Verdict : RShiny
Cost Effectiveness : Depending on your organisation's size and the importance given to a dedicated reporting platform, this might not matter much. However for digital agencies foraying into the data world, emerging start-ups and even budding data enthusiasts who are looking for a sustainable reporting and dashboard solution, a free one definitely makes sense.Â
Verdict : RShiny
Permissions and access : Access control is readily available in Tableau, with the ability to provide different levels of user access. This facility is not available in R shiny without subscribing to its paid service.Vega completely lacks this
Verdict : Tableau