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 Research industry.

Comparisons

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Reviews

(1-25 of 120)
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Score 9 out of 10
Vetted Review
Verified User
Review Source
  • Visualization tool
  • Statistical Analysis
  • Forecasting
  • More flexibility to import tamplates for the visuals
  • More documentation about the formulas
  • More coding automation
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • RShiny applications that are intuitive and help to communicate in the multidisciplinary teams
  • d3.js based visualizations
  • Bayesian statistics
  • calculating confidence intervals
  • merging tables by using SQL commands
  • using regular expressions
  • some of the machine learning implementations are best in R
  • way more hassle-free than SAS, in my opinion
  • open-source - RStudio does not discriminate against people & businesses based on their financial status, many small businesses cannot afford SAS, in many developing countries young people are willing to learn to program, and SAS platforms or other paid software is absolutely out of the question, those people/young programmers will be not able to afford even free cloud SAS due to the internet infrastructure...some of the best ideas come from those who face serious challenges in life and can speak several languages as their minds are often more creative ("necessity is the mother of invention"). I feel that platforms like RStudio or Jupyter connect me with the World, with other creative minds, and contribute to making the World a fairer, better place.
  • something like IronPython in Spotfire, but R equivalent would be great; the existing R interface is not fully functioning
  • something like Pyhon interface in Stata, but R equivalent would be awesome
  • in the pharma World deadlines are tight, pressure is very high - Stata lets manipulate data super fast compared to R
  • brining R and Python community together
  • in my opinion, Natural Language Processing pipelines are better than in R
  • catching up with some of the machine learning implementations - visualization aids in this field are better in Python, at least that is my intuition
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • RStudio IDE makes it easy to combine R and Python in a single data science project.
  • RStudio Workbench launches and manages jupyter notebooks.
  • RStudio Package Manager makes it easy to control and distribute python and r packages.
  • There should be some more featured that needs to be added in Rstudio desktop free version.
  • In compititive market they should focus on more used friendly unique features.
  • User interface needs to be updated
Score 6 out of 10
Vetted Review
Verified User
Review Source
  • Cleaning large datasets
  • Automating the data transformation process
  • Customizing datasets, plots, etc.
  • Unintuitive importing/exporting CSVs and/or datasets
  • Console errors are difficult to understand and not informative
  • Steep learning curve, especially for those unfamiliar with R and programming
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • Easy installation of library of requisite drivers
  • Great for statistical analysis
  • Quick querying and custom analysis to drill down
  • Better inbuilt training to decrease reliance on external resources
  • Parity for Mac and PC users, provide same set of features
  • Bundle R so that it doesn't have to be installed separately
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • Programmable
  • Repeatable workflow
  • Consumes very less resources
  • Statistical analysis
  • Data cleansing
  • Data visualization
  • Modelling
  • Though the UI is far better than other IDEs available in the market yet, it looks more like an old DOS machine.
  • Packages. They are all over the place as there are no evident categories in which they can be arranged. So unless you know the name of the Package, it's really hard to get your hands on it.
  • A little overwhelming. At least for someone who comes from a low coding platform. Although the community is pretty strong.
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • Great statistical packages
  • Good code visualization (formatting/color coding options)
  • Decent integration with other languages
  • Documentation and versioning of the packages can be tedious to track and check for compatibility
  • Requires startup time from the user to learn to use/setup
  • Some features like RStudio Connect are a little buggy/not super smooth
Kunal Sonalkar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • Performing Statistical Analysis is very efficient. With a lot of open source packages available in R programming, data analysis becomes very easy.
  • Publishing web applications and deploying predictive data models is very easy if you have R Server in your firm using Shiny. It can handle large sets of data.
  • Writing data science algorithms like Clustering, Classification and Apriori Analysis is very efficient. The open source nature of this programming language allows everyone to contribute packages to the environment.
  • There are some packages in RStudio which aren't very well known hence its very difficult to get help if you get stuck using them.
  • If the dataset size crosses 20 million rows, then you need extremely high RAM otherwise the processing gets very slow. So in such a case R Server is a must. Cloud storage can be a good alternative though.
  • The graphs which are plotted in the console aren't very intuitive and labels, colors, axis, etc have to be manually written to make the visuals look more appeasing.
Suryaprakash Mishra | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • Dara Management.
  • Descriptive and Statistical analysis.
  • Data science and machine learning.
  • Text analysis.
  • Can not run concurrent sessions and sometimes freezes but can be due to local or virtual machine capacity.
  • RStudio has come a long way, and expect enhancements will continue to improve performance and ease to use.
Chris Beeley | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
  • The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
  • Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.
  • I'm only a data scientist, I'm not DevOps, but I did find RStudio Connect hard to install. I have also tried and failed to get proxy authentication with Apache working, I'm sure it's me being thick but I have never gotten there with it.
  • Another thing I don't like is some of the abstractions in RStudio Connect. There isn't really a file system at all, and data refresh is done with a scheduled RMarkdown report, which is okay but it's a bit round the houses and it's very different from the code on my local machine.
  • I don't love the pricing model of RStudio Connect where you pay just as much for publishers as you do for consumers. I wish we could have, say, 5 publishers and more consumers on our current licence.
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • Notebooks, where you can run chunks and see the output
  • I can view data frames
  • Integration with git
  • Queries to external data warehouses (e.g., using RJDBC::dbGetQuery) are blocking things to the extent that Rstudio freezes and I need to force quit it to stop the query
  • I want to have tools to manage the variables by size
  • Sometimes I want to clean the memory and it would be nice if RStudio suggested an easy way to rank variables by size in the environment
January 18, 2022

RStudio is wonderful!

Score 9 out of 10
Vetted Review
Verified User
Review Source
  • Automate processes
  • Statistical Analyses
  • Portable Code
  • A very good IDE for R programming
  • Can be intimidating to non-programmers
  • I wish I could copy data to the clipboard easier
  • I never have a big enough screen to see all of the data I want to see
Prashast Vaish | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • It's super quick.
  • It has inbuilt functions for most of the analytics procedures.
  • It has great visualizations.
  • It has lots of libraries and sometimes it shows errors while importing them.
  • Its UI can be improved.
  • It takes a lot of time exporting files.
Paul Pulley | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
  • good visual design environment
  • Allows you to quickly see your data set in tabular form
  • Manages package list/download well
  • When rendering a plot, there are several issues bringing it more smoothly to copy/paste it to a slide deck, etc. It is very frustrating that the aspect ratio, etc. visual quality is not consistent from when you originally render to when copy/paste or downloading as a file to later be put in a slide.
  • My resolution changes between laptop mode and desktop mode (plugging into external monitors). In desktop mode I literally have to shut RStudio down and restart/reload/rerun to continue my project. HOW DO I fix this? Is there a way. I've seen a toggle that says it can bounce back and forth depending on device type but it doesn't seem to work!
  • When a program hangs, there is a red stop sign ( I think) in console corner to end the process. This requires, however that I need to complete restart RStudio and restart/reload/rerun etc. Can't it just start but keep all packages, datasets, variables in memory?
Auggie Heschmeyer | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • Keyboard shortcuts
  • Integrating multiple programming languages
  • Providing creators with the resources to develop gold-standard packages
  • I have never been able to successfully replace my SQL editor with RStudio since the SQL drivers are so hard to set up. I would eventually love to be able to use RStudio as a one-stop-shop.