RStudio

RStudio

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Top Rated
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Score 8.8 out of 100
Top Rated
RStudio

Overview

Recent Reviews

RStudio for Business Analysis

9 out of 10
July 18, 2022
We use RStudio as an analysis tool to perform complex data analysis problems and scenarios. We build different statistical models to …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 12 features
  • Visualization (23)
    8.8
    88%
  • Connect to Multiple Data Sources (22)
    8.4
    84%
  • Extend Existing Data Sources (23)
    8.3
    83%
  • Automatic Data Format Detection (22)
    7.5
    75%

Reviewer Pros & Cons

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Video Reviews

1 video

User Review: RStudio Proves To Be A Reliable Statistical Tool W/ Support Avenues In Place If Needed
User Review: RStudio Proves To Be A Reliable Statistical Tool W/ Support Avenues In Place If Needed
02:53

Pricing

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What is RStudio?

RStudio is a modular data science platform, combining open source and commercial products. The vendor states their open source offerings, such as the RStudio IDE, Shiny, rmarkdown and the many packages in the tidyverse, are used by millions of data scientists around the world to enhance…

Entry-level set up fee?

  • Setup fee optional
For the latest information on pricing, visithttps://rstudio.com/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

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Anaconda is an open source Python distribution / data discovery & analytics platform.

Features Scorecard

Platform Connectivity

8.1
81%

Data Exploration

8.7
87%

Data Preparation

8.5
85%

Platform Data Modeling

8.4
84%

Model Deployment

8.1
81%

Product Details

What is RStudio?

RStudio is a modular data science platform, combining open source and commercial products.

The vendor states their open source offerings, such as the RStudio IDE, Shiny, rmarkdown and the many packages in the tidyverse, are used by millions of data scientists around the world to enhance the production and consumption of knowledge by everyone, regardless of economic means.

Their commercial software products, including RStudio Workbench, RStudio Connect, and RStudio Package Manager, are available as a bundle in RStudio Team. These products aim to give organizations the confidence to adopt R, Python and other open-source data science software at scale. This enables data science teams using R and Python to deliver interactive reports and applications to decision makers, leverage large amounts of data, integrate with existing enterprise systems, platforms, and processes, and be compliant with security practices and standards.

The platform is complemented by online services, including RStudio Cloud and shinyapps.io, to make it easier to do, teach and learn data science, and share data science insights with others, over the web.

Together, RStudio’s open-source software and commercial software form a virtuous cycle: The adoption of open-source data science software at scale in organizations creates demand for RStudio’s commercial software; and the revenue from commercial software, in turn, enables deeper investment in the open-source software that benefits everyone.

RStudio Features

Platform Connectivity Features

  • Supported: Connect to Multiple Data Sources
  • Supported: Extend Existing Data Sources
  • Supported: Automatic Data Format Detection

Data Exploration Features

  • Supported: Visualization
  • Supported: Interactive Data Analysis

Data Preparation Features

  • Supported: Interactive Data Cleaning and Enrichment
  • Supported: Data Transformations

Platform Data Modeling Features

  • Supported: Multiple Model Development Languages and Tools
  • Supported: Single platform for multiple model development
  • Supported: Self-Service Model Delivery

Model Deployment Features

  • Supported: Flexible Model Publishing Options
  • Supported: Security, Governance, and Cost Controls

Additional Features

  • Supported: Share Data Science insights in the form of Shiny applications, R Markdown reports, Plumber APIs, dashboards, Jupyter Notebooks, interactive Python content, and more.

RStudio Screenshots

Screenshot of RStudio runs on most desktops or on a server and accessed over the webScreenshot of RStudio supports authoring HTML, PDF, Word Documents, and slide showsScreenshot of RStudio supports interactive graphics with Shiny and ggvisScreenshot of Shiny combines the computational power of R with the interactivity of the modern webScreenshot of Remote Interactive Sessions: Start R and Python processes from RStudio Workbench within various systems such as Kubernetes and SLURM with Launcher.Screenshot of Use Jupyter: Author and edit your Python code with Jupyter using the same RStudio Workbench infrastructure.Screenshot of RStudio Connect makes it easy to deploy Interactive Python Applications (including Dash, Bokeh and Streamlit), in the same place you share your Shiny apps.

RStudio Videos

Open Source Software for Data Science - CEO J.J. Allaire provides an overview of RStudio's mission, and why we've become a Public Benefits Corporation.

Watch Overview of RStudio Connect

RStudio Integrations

RStudio Competitors

RStudio Technical Details

Deployment TypesOn-premise, SaaS
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo

Frequently Asked Questions

Anaconda, Dataiku DSS, and Cloudera Data Science Workbench are common alternatives for RStudio.

Reviewers rate Visualization highest, with a score of 8.8.

The most common users of RStudio are from Enterprises (1,001+ employees) and the Hospital & Health Care industry.

Comparisons

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Reviews

(1-25 of 75)
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Score 9 out of 10
Vetted Review
Verified User
Review Source
We think the open source version is good enough for the task we are currently doing. R Studio open source offerings are very complete and only in some cases would be necessary other packages.
Score 10 out of 10
Vetted Review
Verified User
Review Source
1. it does not discriminate against creative minds based on their financial status 2. it is easier to create a pilot tool to show to the stakeholders/customers first, before requesting any funding 3. it is a more reliable, convenient way of running the business, as not linking the access to RStudio directly to money allows for creating good, long-term business relationships (again, my personal opinion based on my individual experience and observations/thoughts)
Score 10 out of 10
Vetted Review
Verified User
Review Source
Open source means easy collaboration and interaction with people who invest much time and energy developing the tools, which then provides a sense of reliability and trust when using the tool. It also provides an opportunity to participate in the process of developing a better tool with a community, which would end up benefiting everyone in their work. It is a virtuous circle for improvement for the entire R community.
Score 8 out of 10
Vetted Review
Verified User
Review Source
There are many resources out there for open sources packages, and it is free to use. The good thing about open source in data science is transparency and flexibility. We can see how the packages are written so we know the underlying assumptions in the models and how we can customize them for our needs. Data science is a quickly developing field. We need the flexibility and adaptability of open source tools to implement changes quickly when new research comes out and not rely on large corporations to update their products.
Score 6 out of 10
Vetted Review
Verified User
Review Source
I believe I use RStudio's open-source offerings, though I'm not entirely sure. I use libraries, such as ggplot, which I have found from Googling my question. I mostly use these tools to streamline the data analysis process, which helps me explore the tool and complete my project goals efficiently.
Score 10 out of 10
Vetted Review
Verified User
Review Source
We don't use Shiny at the moment since all the front-end visualization is based on the Tableau platform. The main reason for using RStudio was the cost to performance ratio. Believe me, when your denominator has 'free' in it, and the quality of the product is not sub-prime, you've got a great performing software at your disposal.
Score 8 out of 10
Vetted Review
Verified User
Review Source
The open-source offerings are well maintained. They offer a set of functionalities that would be difficult or time-consuming to implement on an individual basis, so they offer us major time savings. The main advantage I see in open source data science is that it'll reduce duplicate work and enable wider use of these tools and for these tools to be able to iteratively improve with the input of these users as well.
Chris Beeley | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
I work in publicly funded healthcare and open source is a vital tool to allow us to do complex work cheaply. We use open source because it's cheaper and better and we publish our own source code and contribute to open source repositories because it's the right thing to do and it improves the space for everyone, including us.
Bobbi Woods | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
I have primarily used RSiena, which is an advanced social network analysis package. I think the value in open source data science is, other than the very low cost, the availability of learning resources to users who hit a roadblock. Being able to search the internet for solutions to common issues is invaluable and definitely an underrated part of using a popular open-source tool.
January 20, 2022

Hooray RStudio.

Score 8 out of 10
Vetted Review
Verified User
Review Source
Shiny is a great tool, and it provides an easy approach to develop a dashboard without much web developing experience. I absolutely love the open source community since people are consistently throw new ideas and provide feedbacks as well. That's how things can get better. Love it!
Jacob Benzaquen | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
I use rayshader as my primary package for creating maps and it is remarkable. It is beyond easy to create any 3D map terrain or develop 3D maps from existing topographic or geologic maps to make the experience easier to read and understand for the customers that we work with.
September 11, 2021

RStudio for R!

Score 9 out of 10
Vetted Review
Verified User
Review Source
It allows for grassroots movement and demonstrate the value of analytics products, built on open-source software, to management prior to investing on commercial version.

We were able to grow the community of developers and users internally and boost data and programming literacy for non-coders, which paved ways to more ideas for analytics problem/solution.
Score 10 out of 10
Vetted Review
Verified User
Review Source
I use RStudio, which is the IDE of R. RStudio primarily acts as a much more modern and user-friendly platform. With the four major panels (environment, plot, console, and script) easily laid out so that you can check all the information for your analysis easily and quickly. I also use a variety of packages. The biggest advantage of these is that you do not need to learn an entirely new form of data analysis or advanced math to perform an analysis. Instead, you can quickly call the function and proceed with your analysis.
Score 8 out of 10
Vetted Review
Verified User
Review Source
Being a large corporate company we were not eligible for using the open source version of this software suite. However, there is huge value in the open source data science community as a whole. Chances are that there is a team or developer out there who has released a package that contains a function or calculation that you need. With the community contributing as a collective this should mean that the quality of everyone's apps accelerates quicker than they would under a closed model.
Heramb Gadgil | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Open source has a huge community associated with it. This makes the development of a solution easy, as there are numerous SMEs to help you out. Also, the issues/errors are resolved quickly.

The Public Package manager (open-source) has been an enormous success for installing packages that required compilation earlier.
B. Mark Ewing | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We use a mix of commercial and open source offerings. Because RStudio provides most of their products as FOSS, it's hard to justify the licensing costs unless there are significant or critical features included. The IDE is a wonderfully functional tool, and the open source server version integrates with local security such that we have secure development environments for our data scientists. There simply is no reason to pay for the commercial licenses. Open Source Data Science allows for faster implementation of cutting edge ideas and provides an avenue to correct issues when they arise.