RStudio is the Swiss Army knife of R Solutions
Updated September 04, 2021

RStudio is the Swiss Army knife of R Solutions

B. Mark Ewing | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with RStudio

RStudio provides a number of products and services, from their best-in-class IDE for R to their collaboration and publication platform, RStudio Connect. Our Data Scientists leverage RStudio Server on a daily basis to do analysis, develop dashboards and Shiny applications. They deploy these to either our Shiny Server Pro environment or, more commonly, our RStudio Connect environment. Others at the company use the RStudio IDE to do analysis on their local machines. R, as a statistical programming language, is mostly commonly used by our data scientists who support the whole organization, often in a paired environment. By using RStudio Server we can ensure consistent environments for deployment of assets and ease of managing security. There are pockets of other scientists, marketing and logistics analysts who use R to amplify their work and they use the desktop IDE because they have no need for collaboration.
  • Excellent integration of both R and Python IDEs in one.
  • Simple publishing of dashboards and applications from RStudio IDE to RStudio Connect.
  • Integration of package management with projects to support collaboration.
  • Excellent contributors to the R Open Source community, really invested in its health.
  • Support integration with Enterprise AD environments for security.
  • Python integration is newer and still can be rough, especially with when using virtual environments.
  • RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
  • Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
  • Our spend on RStudio products is fairly low, yet has a significant impact on the productivity of our Data Scientists.
  • Shiny Applications we've deployed have enabled us to avoid needing application developers on projects while still delivering highly interactive, beautiful solutions.
  • The pricing model on RStudio Connect has greatly limited our ability to roll it out to broader audiences.
In the space of data science tools, code is king. It enables use of standard version control systems like git, access to a wealth of expertise via StackOverflow and others, is commonly used in modern education programs, and more. Other solutions in this space are built on expensive, proprietary systems with limited options for deployment. We selected R over Python due to a lower security risk profile and higher levels of internal expertise due to the schools we recruited from. RStudio is the only commercial choice to support the development of R in the enterprise.
RStudio provides a host of FOSS and Commercial offerings, so it has well suited offerings for almost every level of use. Their FOSS IDE and 'tidyverse' packages are well suited for individual analysts. The server offerings are easy to spin up for small departments with a high need for consistent environments to enable collaboration, their tools like 'renv' and 'packrat' further assist with collaboration by making it easier to spin up consistent environments. Their publication environments of Shiny Server, Shiny Server Pro,, and RStudio Connect have a host of pros and cons. Shiny Server, while free, doesn't provide a real identity management / kerberos style security, so it would only be appropriate for non-sensitive solutions. Shiny Server Pro is the commerical offering that can be configured to provide real identity management out of the box. It's licensing model is based on concurrent users which makes it well suited for a highly transitive department-ish sized solution. RStudio Connect is a far more elegant product than Shiny Server Pro, but prices based on named users greatly limiting the scope of impact it can have.

Using RStudio

20 - Mostly professionals in our Data Science department including Statisticians, Machine Learning Practitioners, and Operations Research professionals. There are individuals with the necessary programming skills to take advantage of it in our Marketing and Market Research groups, as well as Chemists/Chemical Engineers who use it in our chemical Technology area.