RStudio provides stable and trusted open source tools in a market frequently flooded by trendy and soon-to-be abandoned software
Updated September 01, 2021

RStudio provides stable and trusted open source tools in a market frequently flooded by trendy and soon-to-be abandoned software

Jeff Keller | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with RStudio

We use RStudio Connect as a publishing platform for R and Python documents, apps, and APIs. It provides us with a professional, clean looking interface to share our work with internal clients and stakeholders. Our usage began within a relatively small team, but the popularity of RStudio Connect and its features saw that usage grow to a broader group of users that spans multiple departments and business units.
  • Excellent Documentation
  • Well-designed Features
  • RStudio Connect could really benefit from containerized environments to enable isolated, reproducible content.
  • RStudio Connect's pricing model is a little frustrating at times. Infrequent consumers of content cost the same as heavy users who publish content regularly. This limits our ability to share the work of our data scientists at a reasonable cost. We would much rather pay more for each "publisher" seat and have much cheaper or free "viewer" seats. This would also likely lead to a greater investment in RStudio Connect on our part, as we would be able to expose the platform to more team members and key funding decision makers.
  • Making data science content readily accessible on an intuitive platform has made the work we do less mysterious to our clients/stakeholders
  • Clients/stakeholders find engaging with the company's data science function more enjoyable since they have greater visibility into our work via RStudio Connect
We use RStudio Connect over Domino for publishing content because it is much more flexible and user friendly. It also "just works" far more often than Domino. RStudio Connect has much better support for API-type content, such as OpenAPI/Swagger documentation. For interactive web apps, RStudio Connect offers the data scientist more controls in a more intuitive interface to manage processes, load balancing, and URL paths. Domino either has 1) no such functionality, 2) an unintuitive interface, or 3) functionality that is only available to administrators.
RStudio's online documentation is among the best you will find for any software product, and especially among data science tools. RStudio Connect is no exception here. RStudio's email support and Customer Success representatives are responsive and considerate, typically responding to inquiries within 24 hours. Those responses were formulated by someone who clearly takes the time to read and understand the request/issue enough to offer useful assistance.
Open source software (including data science tools) is more stable and reliable in the long run so long as there is a community of users. Proprietary software may have short term benefits (e.g., bespoke support, higher performance) but invariably, deviates from what the end user actually needs in the pursuit of profit. This might come in the form of anti-features, vendor lock-in tactics, or other under-handed methods (e.g., malicious telemetry). RStudio's commitment to open source software means they are in it for the long haul. This is music to a data scientist's ears--knowing that your work will continue to work (and be reproducible) for years to come, without the artificial hurdles we are all so accustomed to with proprietary software.
RStudio Connect provides a common publishing platform for all of our R and Python content (e.g., documents, apps, APIs). This type of content is incredibly valuable for communicating complex ideas that would otherwise languish in esotericity on a blackboard or in an un-digestable, un-sharable format on a data scientist's computer. Having a single location where data scientists can publish--and their stakeholders can view--such content drives more engagement and trust among data scientists and between them and their stakeholders.
We use RStudio's public Package Manager instance to speed up build/compilation time of our Linux compute environments. Building R packages from source can be computationally and time expensive. The fact that RStudio has built these packages for a variety of Linux platforms and CPU architectures is a boon to the wider R community.

Do you think RStudio delivers good value for the price?


Are you happy with RStudio's feature set?


Did RStudio live up to sales and marketing promises?


Did implementation of RStudio go as expected?


Would you buy RStudio again?


With a small investment, RStudio Connect is a great platform for sharing computationally inexpensive or static data science content. For more complex or dynamic content, a more significant investment is required. And it is not just a monetary investment. RStudio does not currently offer hosting or infrastructure architecture services, so the burden of setting up and maintaining the platform is entirely on the user. RStudio Connect (and other RStudio products) leverage a lot of open source software, which enables a great many things, but it also means that the user is required to understand a number of different technologies and how they fit together. Users looking for a turn-key solution will likely be disappointed in the amount of effort required of them to get started.

Using RStudio

100 - The heavy users of RStudio products in our organization are primarily Data Scientists, Product Analysts, and Business Intelligence Analysts. However, each of these groups have stakeholders located in just about every part of the business, and RStudio Connect is the platform we use to share our work with these audiences, resulting in a very wide range of backgrounds that ultimately interact with Connect.
1 - A Linux administrator is necessary to support RStudio Connect. In our case, an experienced Data Scientist (myself) who has a lot of personal experience with Linux provides this support. In addition to Linux knowledge, a support person needs to be familiar with the types of computing challenges that Data Scientists and Analysts face in their day to day work, so that they can properly configure RStudio settings to best fit these needs.
  • Scheduling jobs
  • Deploying web apps
  • Deploying APIs
  • Using scheduled RMarkdown documents for data ETL
  • Deploying a shiny app dashboard to monitor a competing product's performance
  • Deploying product quality APIs
We are planning to renew our Connect license in the next few weeks. Connect provides an easy to use, feature rich, stable, reliable, and price competitive platform for publishing and sharing the amazing work our Data Scientists and Analysts are producing. Renewal is a no-brainer.
RStudio is providing professional tooling for our Python users as well. Before Connect, no Python-based API had been deployed anywhere beyond a tinkerer's laptop. RStudio's decision to make Python a first-class citizen in its suite of products is a big deal. Data Scientists now have more flexibility and can more easily choose the right tool for a given job.

Evaluating RStudio and Competitors

  • Product Features
  • Product Usability
  • Product Reputation
Usability is a very important element of our decision to go with RStudio Connect. Many alternative software offerings are bloating with half-baked and ill-fitting features, often with lots of redundancy (e.g., many ways to do the same thing). Connect provides a single comprehensive and flexible path to accomplishing a task. This allows Data Scientists to focus on their work rather than learning the nuances of an overly complex tool.
If we had to evaluate these products again, we would add an additional criterion to our rubric that captures the ease of deployment across a federated cloud organization. At the time, we were a single team operating in a single AWS account, but the success and adoption of RStudio Connect has seen the incorporation of other teams across our company. These teams have their own AWS accounts with their own permission rule sets. We would now ask: "How easily can we deploy something like RStudio Connect either across these federated accounts or in such a way that content published to Connect can access other AWS accounts while adhering to security best practices?"

RStudio Support

Quick Resolution
Good followup
Knowledgeable team
Problems get solved
Kept well informed
No escalation required
Immediate help available
Support understands my problem
Support cares about my success
Quick Initial Response
RStudio provides the same level of support for all of its paid offerings, so we did not need to choose whether to pay for support or go it alone.
Yes - When reporting bugs to RStudio the response is swift, as are all responses to support tickets we've opened. In the case of bugs, RStudio has been great at acknowledging the problem, working with us to identify alternatives and workarounds, and ultimately putting the fixes on their development roadmap. They have also been good at communicating the status of any potential fixes.
During an evaluation of RStudio Server Pro (now called Workbench), I opened a support ticket asking about whether an advanced feature described in the Admin documentation could be used to achieve a particular behavior. Not only did RStudio confirm that yes, this could be done, but they also acknowledged the value in using the feature in such a way and even went so far as to provide a working example of how to do it!

Using RStudio

Like to use
Relatively simple
Easy to use
Technical support not required
Well integrated
Quick to learn
Feel confident using
  • Scheduling reports
  • Setting up email notifications
  • Configuring content runtimes
  • Deploying RStudio onto a cluster
  • Identifying environment differences between Connect and the client machine