RStudio Reviews

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Score 8.8 out of 100

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TrustRadius Top Rated for 2020

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Reviews (1-25 of 87)

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January 06, 2021
Carlos Celada | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
The main user of RStudio is the business analytics team. The risk team has started using the product a couple of months ago. There are two use cases for RStudio inside the organization:
  1. Data analysis and development of statistical / machine learning models.
  2. Development of information dashboards in the form of shiny applications, which are being deployed using RStudio Connect
  • Provides both R and python development environments, which can be deployed to RStudio Connect
  • Authentication integrated with enterprise solutions
  • Well documented for end users and administrators
  • Git integration for code versioning
  • Project sharing is a great feature, but only works if RStudio Server is configured to use local accounts, not when using other authentication methods
RStudio products are great for technical teams / team members. The integration of both R and python in a single product allows developers to make use of their preferred language for data analysis. Those team members who are analytical but do not have a technical background won't be able to fully use the products; for them it's better to have a different tool for exploratory analysis and BI.
Read Carlos Celada's full review
December 23, 2020
B. Mark Ewing | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
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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.
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, shinyapps.io, 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.
Read B. Mark Ewing's full review
December 18, 2020
Flavio Leccese | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
We use RStudio Connect for deliverying data science product (dashboard and documents) across all companies and areas of the group.
So far have been addressing several business problems concerning HR analytics, sales optimization, stock optimization, database automatic consolidation, utility expenditure forecast. Many other projects are ongoing exploiting the APIs provided by the platform
  • Easy to use. Not only for power user but also for people who need a reliable platform to deliver contents.
  • Very versatile. There are many tools that can serve the scope of communicating results.
  • Constant updates and newsletter keeps you on the track.
  • Management of some deeper aspects of the platform is not a so straight-forward, especially when it comes to deal to customization (connections, packages management...).
  • Administration console may be a bit richer, making available of some operations that you may be interested on doing by user interface and not by shell.
  • Deploying apps is still a bit problematic for some particular (rare!) packages, make it easier to install packages not from the CRAN.
Talking about RStudio Connect, we felt very comfortable using it from the first moment. With a very low effort you can kick project, distribute results across the organization through catchy apps. This brings a lot of value (considering the license cost and comparing it with the analogous software for data science). So, scenarios in which you have to be fast, agile but still not dirty.
On the other hand, when it comes to structuring a more complex architecture in which RStudio Connect is only a part of it, it becomes more complicated. Of course we must say that we have received a lot of support in doing that!
Read Flavio Leccese's full review
December 13, 2020
Terry Leitch | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
I'm using RStudio in developing and delivering supporting course materials for machine learning and big data. It's a great resource, and the fact that I can use both R and Python in the same familiar IDE has made this a killer app for me. The majority of course material for Python has been developed and distributed via Jupyter Notebooks, which is not an IDE. The ability to do end-to-end development in one place, using the best of both worlds (plus C and C++), make RStudio the best choice for anyone who want to develop robust ML/AI applications.
  • Great IDE
  • Multiple language support
  • Github integration
  • Shiny integration
  • Python integration
  • C and C++ integration
  • Project tools
  • Graphics
  • Integrated debugging tools
  • Multiple versions of R can be confusing to maneuver
  • Quick view of library locations relevant to the R version in use would be a good resource and reduce confusion
  • Better online publication options for quick release, small apps by students
  • Big data model generation
  • Financial time-series applications
  • Hybrid R/Python development
  • Cluster analysis
  • AWS cloud
  • Rapid prototyping/rapid development
  • New analysis tool development and distribution
Read Terry Leitch's full review
December 04, 2020
Sean Corbett | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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RStudio is presently used heavily across several departments in our organization. In Data Science, we utilize RStudio and its related products for analysis of both early- and late-stage biomedical data for drug development. Our Biostatistics group uses RStudio for analyses related to population-wide trends in results from our ongoing clinical trials.
  • Software project management
  • Software package development
  • Report publishing
  • Real-time collaborative editing
  • More responsive RStudio Sever UI
  • Launcher integration directly with Spark clusters (especially via third parties like Databricks)
RStudio is generally well suited especially for exploratory analysis in a computational biology setting, as well as as a Python IDE for developing more robust production code that might need to integrate tightly with R. RStudio is less appropriate as an IDE for other languages beyond these two (for obvious reasons).
Read Sean Corbett's full review
December 02, 2020
Ethan Kang, FCAS, CSPA | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is being used in the Underwriting and Analytics Department. We publish our analytics artifacts through RStudio Connect, then users from other department can consume with ease.

We help our colleagues to better understand the financial health of the company through profit and loss evaluation, risk underwriting and portfolio review. RStudio helps us bridge the gap between Data and Solution, we tell story through data visualization and reproducible analytical documents that are easy to grasp by our colleagues.
  • Great selection of libraries to do statistics, machine learning, data visualization, interactive dashboards
  • RStudio Connect makes sharing your work with your colleague a breeze using one-click publishing.
  • The ability to connect R with other languages like Julia and Python all within the same working session helps generate more creative ways to solve problems. We can use Julia in R to speed up intensive calculation, or we can use Python Tensorflow or Pytorch in R to do deep learning.
  • R has a great community on social media and stackoverflow so it's very easy to learn from the other users.
  • The learning curve may be a little steep for new R users
  • There are multiple ways to solve a problem. For example, there are mlr3 and tidymodels to build predictive models, and there are tidyverse and data.table to perform data cleaning. It could be confusing and overwhelming for new users to decide which libraries to learn and use.
RStudio is great at reproducible research, data visualization, dashboard and REST API, and build predictive models.

R is single-threaded, so it may not be suitable when you need to scale your application to many users. For example, if you have a shiny app with R, the performance may slow down when multiple users are in the app. People are addressing this issue in several ways, however, so this may not be a deal-breaker.
Read Ethan Kang, FCAS, CSPA's full review
December 01, 2020
Jeff Keller | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
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.
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.
Read Jeff Keller's full review
November 24, 2020
Jeremy Allen | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
My team uses RStudio on data science projects within IT, but also to support other data science projects across HR, Finance, Marketing, and external customer contracts. Examples include predicting maintenance on PC assets, analyzing vendor spending, topic modeling and text analysis on internal surveys, and more. We also write R code that assists our data engineers with creating data integrity scores and cleaning data.
  • RStudio excels at customer engagement.
  • RStudio is very responsive to customer needs.
  • RStudio cultivates one of the best tech communities that is safe and inclusive.
  • RStudio could do more to provide easily consumable and sharable enterprise use cases that demonstrate the benefits of the enterprise apps.
RStudio is well suited for individual analysts as well as teams and server environment. Perhaps more could be done to integrate with enterprise environments that are dominated by Windows architecture.
Read Jeremy Allen's full review
November 24, 2020
Brandon Farr | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio supports the development of internal business intelligence tools and reproducible reporting within our firm. It is used by two members of our Investment Team. It helps us efficiently produce and maintain numerous coding projects that support all of the investment decisions that we make. RStudio has been integral to our firm developing tools that typically only exist at firms much larger than ours.
  • Organizing code - via projects
  • Developing reproducible reporting - via seamless integration of RMarkdown
  • Increasing efficiency of analysis - via "Find in Files", code reformatting, etc.
  • It's gotten better, but code debugging still feels substandard (cf. Visual Studio Code)
  • The workspace layout feels a bit stale compared to other environments, I spend a lot of time resizing panes.
  • Addins seem powerful, but difficulty with discovery and use has kept me from using them much
For coding in R[Studio], there is no other tool I could recommend more highly. Between the work put into the RStudio application itself and the deep integration of RStudio built packages, no other environment comes close to being as useful.
Read Brandon Farr's full review
November 04, 2020
Matthew Stewart | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is being implemented by our analytics department to help solve complex client problems by utilizing the data and statistical packages available through RStudio. The ability to perform far more accurate multi-linear regression models and time-series forecasts has helped our clients not only see where they are going in terms of sales but also what affects their sales.
  • Data Organization
  • Multi-Linear Regression
  • Data Visualization
  • Time-Series Forecasting
  • As a scripting language, it is not a pick up and go platform. You need to spend the time to learning the program.
  • Platform versions and Package versions often do not align.
  • Would love to see standard templates that would generate a basic code for statistical models. This could save time and help newer users learn how to operate the program.
RStudio is a fantastic program for anyone looking to do data organization, visualization, or statistical analysis. It excels if your team is looking to take a heavier investment into a complex platform. RStudio does not have a native spreadsheet editor and newer users will have to learn how to edit their data in the platform.

This is NOT a pick up and go platform as we are used to. It has hundreds of advantages and can be customized to near perfection. Yet, it will require many hours of investment. I would suggest looking at other pre-built platforms if the team is smaller.
Read Matthew Stewart's full review
January 04, 2021
Yaxian Xie | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
It's being used as preferred tool by some data analysts/scientists. I use it for data transformation and simple stats analysis (e.g. a/b testing, linear regression, exploratory analysis, etc.).
  • Data manipulation, easy and handy.
  • Exploratory analysis, nice plots.
  • Simple stats analysis, t test.
  • Output format, it could be better so we can easily add output to a doc/ppt for sharing.
  • Error message, it could be more informative.
  • Data processing, it gets slow when data is big (e.g. millions of rows).
Pros: easy to use on local machine, handy libraries, flexible for data manipulation and simple stats analysis.
Cons: output is less friendly for sharing, not well integrated with most internal ML prod systems, requires commercial license for internal use, it takes time for new users, slow to process large datasets.
Read Yaxian Xie's full review
December 23, 2020
Jessica Willard | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
R Studio is used in conjunction with R Package Manager and R ShinyApps.io for data cleaning, preparation, and sharing with partners.
  • R Studio is particularly good at performing quality assurance checks on data sets.
  • R Studio is better than some other software at allowing the user to quickly test the data for coding errors.
  • R Studio allows the user to reduce the number of lines of code to perform functions.
  • More support for packages.
  • Faster loading times.
  • No suggestions.
R Studio is really good at creating code for testing and preparing data sets, but not great at integrating with other software platforms.
Read Jessica Willard's full review
December 18, 2020
Leo Nootenboom | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
RStudio is used by multiple departments in our organisation mainly in the R&D area, quantitative genetics, breeding and bioinformatics.
  • RStudio staff is very knowledgeable and supportive.
  • The product documentation compared to other products we use is very good.
  • Product roadmap is interesting and suits our future needs.
  • For me the RStudio Launcher documentation (slurm/kubernetes) is not as clear as the rest. I had to put serious effort and a lot of trial and error to get all parts working.
  • Admin web interface should provide clusterwide information - not per server.
  • Developers are struggling to find a good way of working with tools like plumber & postman (web api) that start a locale service within RStudio server.
  • Similar while switching from local IDE to RStudio Server Pro some developers ran into issues using oauth authentication flows.
Most of the time I would recommend RStudio server:
  • Integration with slurm, ability to run jobs that could not be run on a local workstation/laptop.
  • Not have to troubleshoot local installations (dependency issues), sort out once on a central installation.
  • Integration with external authentication.
  • HA setup.

Less appropriate:
  • Less suited for developers who are used to have full freedom to do whatever they want on their workstation.
Read Leo Nootenboom's full review
December 16, 2020
Nate Kratzer | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
It is used by our Advanced Analytics department. We use it both as an IDE for individuals as well as using RStudio Connect and RStudio Server Pro. RStudio Connect allows us to easily deploy shiny apps, rmarkdown documents and jupyter notebooks. RStudio Server Pro allows us to easily use RStudio in a server environment. Essentially RStudio lets data scientists do their work and share their work without needing an entire team of data engineers to support them.
  • Brilliant IDE for coding.
  • Easy publishing of apps and documents.
  • Ease of use for data engineering team.
  • It's consistently growing Python support, but there is still some room to grow here to make it a truly bilingual platform for data science. That said, it does server our Python users fairly well, even in its current form.
RStudio Connect is pretty easily the best simple publishing solution I've worked with for sharing data science apps.
Read Nate Kratzer's full review
December 16, 2020
Heramb Gadgil | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Most of the DNA teams within our organization are using RStudio right from data pulls to visualization & reporting. UI/UX for shiny applications has been phenomenal and has been utilized in broader initiatives that enabled huge dollar savings. 'RMarkdown' has eased report generation to a great extent and 'odbc' drivers have made connecting to databases an easy task.
  • Abundant development on statistical and data science libraries.
  • Interaction with other programming languages and BI tools.
  • Customized application building and reporting framework through shiny and markdown.
  • Simple IDE with competent and robust functionalities.
  • Strong and active community.
  • Highly approachable core members and teams @Rstudio.
  • Integration with Google Cloud Platform.
  • Flexibility of choosing a remote R-interpreter (as is present in IntelliJ/PyCharm).
  • Memory issues and slowdowns when it comes to working with large datasets.
  • Orchestration of production workflows with Airflow.
  • Production pipelines for RStudio Connect content.
Most of the DnA use-cases are handled perfectly well with RStudio eco-system. Tidyverse, tidytext, ggplot2, shiny, Rcpp, rJava and numerous other statistical libraries are robust to handle all the stages of a data analysis pipeline. Seamless integration with Javascript, CSS and JSON enriches the visualizations in shiny application. If your project involves moderate sized data pulls, R (RStudio) is a go-to solution without much of a thought.

It still needs to catch-up in terms of cloud platform integration and ML pipelines.
Read Heramb Gadgil's full review
December 15, 2020
Peter Higgins | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
[Used for] Data management and data analysis in research.
  • Data wrangling
  • See the data and the environment in IDE
  • Rmarkdown output in many forms
  • Readable code
  • Addins
  • Rainbow parentheses
  • Encourages open community & diversity
  • Fun conference
  • Segregation between high end and open source
  • Need a clear Shimano-Style trickle down timeline of technology - so that what is available for Pro premium now should be in the open source version in N (5? 10?) years.
  • Help teach new, diverse community to become coders and package-makers - pretty good now, but still fairly jargon-y and a steep learning curve. More resources to reach more people & move them from Excel to reproducible research.
  • Make writing functions in the tidyverse cleaner and easier. Tidyeval is still a bit of a mess. Much better with curly-curly, but still many exceptions. still a ways to go.
  • Ggvis is a neglected appendage. Should it be retired? is there a newer, better framework for interactive plots that can be used?
  • Embrace open source package developers who do great stuff, like flextable. Too often RStudio uses its bully pulpit to overrun existing packages (patchwork > cowplot, gt > flextable). Embrace these folks and bring them into the fold (well done with Claus Wilke. Would like to see something like that with David Gohel.
  • Would like to see a semi-automated workflow to take a dataset and generate oxygen documentation for each variable.
Sharing data, reports, plots in word and ppt works great.

Not great (lots of barriers to entry) for Excel users. They can "code" - lots of complex formulas. But lots of entry processes are not great. Just installing Rstudio has ~14 screens of yes/no/default clicks. Better to have an option for "just give me the standard install" with a lot fewer clicks.
Read Peter Higgins's full review
December 12, 2020
Esther Kukielka - PhD, DVM, MSc | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Anyone within CDC is able to use RStudio. As I am working in Public Health in USA, and many people use SAS because it is that they are used to. However, with the data modernization push the CDC is doing, more and more people are interested in using R and RStudio.
  • Autocomplete
  • Git tab
  • Project options
  • This could be because I simply don't know how to do it, and may not be a RStudio issue, but when I try to read files that are behind the firewall, everything runs very slow. Also, I cannot have Rmd files behind the firewall: they simply don't run. Also, I cannot get the Git tab to work if I am working behind the firewall.
  • Unstable: It crashes without knowing why.
  • I don't think RStudio has the capability of coding at the same time with your coworkers on the same script/project.
Very good for reproducible research - although the different R packages versions could be a problem (I tried working with Renv and my whole R and RStudio crashed: I had to uninstall everything and install it again). But I guess this is more an R issue, not so much RStudio? Maybe RStudio could check that libraries need to be updated so nothing crashes. It could also recommend a set of packages versions that would work together in your code.
Not that good for working collaboratively simultaneously.
Read Esther Kukielka - PhD, DVM, MSc's full review
December 07, 2020
Nicolò Manca | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
Our Data science department is a central team that uses RStudio IDE on own computers for developing projects and products. Products (app or api) are deployed using a professional version of RStudio Connect and are available for the relevant employee at the company. IT department manage the hardware needed for the solution to run. We are in charge of business, development and software architecture.
  • Simplicity in managing code and projects.
  • Easy git integration.
  • Deployment of services both on .io and on Connect.
  • Editable and downloadable dataframes in the viewer.
  • More flexible file management in the file tab.
  • More deeper dataframe exploration options in the viewer.
Well suited for people approaching to coding and looking for a tool for data analysis and visualization especially in a business-centric scenario and with low IT knowledge/support.

I don’t see scenarios where it is inappropriate when using R.
Read Nicolò Manca's full review
January 16, 2021
Sridevi Patil | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
I work in an educational institute. RStudio is used to study R language for statistical computing. It is an IDE that can be a desktop application or used remotely using web browser. It enables learning and implementing statistics through programming. It makes statistical computing easier, as many programs do a good job to implement functionality but no statistical support.
  • It is a cross-platform IDE supporting R language
  • Enhanced support for statistical computing
  • It is an open-source scripting tool allowing simple scripts to do the work instead of long programs.
  • Interface is not very overwhelming; GUI can be improved
  • Support for gaming is limited
  • Analysis of big data using RStudio is challenging
RStudio is well suited for learning R language. It is less appropriate when need to do complex data analysis. Python seems to be a better option compared to R language that is supported by RStudio.
Read Sridevi Patil's full review
December 28, 2020
Rohit Khandelwal | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
RStudio Bundle is presently being used in our department with-org., Group Management Systems - Analytics. In Data Science, we utilize RStudio Server, Connect and Package Manager to perform analytics on various data with-in our project and it is also being used by various other project with-in our org. We can use both R and Python in the same familiar IDE, it is very much likable with various users.
  • It makes it simple to develop and reuse code.
  • It have a simple to use interface.
  • Easy git integration.
  • Unstable: It sometime crashes.
  • Setup can be complicated.
  • Sometimes very slow.
RStudio is very well suited for data analysts and statistician. RStudio is suitable to perform analyses in terms of Data related projects. Whether it's predictive analytics, descriptive statistics, or graphical summaries it is a tool that can deliver. A large number of packages are supported to enable all kinds of projects: time series analysis, visualization, table-building, advanced statistical analysis are all examples of RStudio's application. It is currently the best option for developers to write code in R programming language.
Read Rohit Khandelwal's full review
December 04, 2020
Ning Rui | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is being used by majority of researchers and analysts across the whole organization. It is being used to conduct statistical analysis, predictive modeling to address various business problems in operations, talent management and performance assessment.
  • Data query
  • Statistical modeling
  • Data visualization
  • Data cleaning and imputation
  • Learning curve is a bit steeper for beginners
  • Better data visualization tools
  • Set up can be complicated
RStudio is well suited for predictive models and model diagnostics. However, it might not be particularly efficient for sharing scripts for reproducible analysis.
Read Ning Rui's full review
December 03, 2020
Rodrigo Pérez Romero | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is being used in a specific department, Business Analytics. It is used to develop shiny dashboards for many commercial areas to track a lot of different KPIs. It is also used to develop analytical models like logistic regression or decision trees to predict churn or the next best offer to recommend to our customers.
  • It makes collaborative work easy.
  • It makes it simple to develop and reuse code.
  • It have a simple to use interface.
  • More tutorial on how to use the interface.
  • Help for predictive code writing.
  • A better place to visualize images.
I'm an R and RStudio fan; it is a language I enjoy using, and RStudio is the best platform where you can develop while using R. It helps a lot and makes your work a lot easier.
Read Rodrigo Pérez Romero's full review
December 02, 2020
Ermias Amene | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is being used across the agency for data analysis, data visualization, data management, and preparation of report. I have specifically used it for analysis and visualization of data and for training purposes.
  • Data visualization
  • Reporting and dashboarding (e.g., Rmarkdown, RShiny)
  • Ability to easily publish outputs to the web
RStudio has dropdown menu that can help to easily perform common tasks such as setting a working directory, downloading packages, or even importing data. It is well suited to create dashboards using RShiny and it provides a superior platform for data visualization.
Read Ermias Amene's full review
November 17, 2020
Emilio Cabrera | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We model economic indicators for border cities in Mexico.
  • Coordinate data wrangling with visualizations
  • Interactions with other software
  • Project management
  • Function name autofill
  • Speed
  • More and clearer detail on dashboard bugs
Communicate data insights in a clear and swift way. Code is easy to debug. It is very intuitive and hence, easy to learn.
Read Emilio Cabrera's full review
December 22, 2020
Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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We use RStudio for development within bioinformatics group. The product (R Shiny) from our group is used across the whole organization, it is used for data integration, both clinical and pre-clinical biomarker data and other types of data integration.
  • Best IDE for R programming.
  • Good ecosystem for R Markdown and R Shiny.
  • RStudio Connect is very useful for publishing and user authentication.
  • It could have its own consulting team to support company to build R related products instead of partnering.
  • It could also offer tailored paid training for small and large companies.
RStudio is definitely the best for coding in R. It significantly enhances the efficiency and shortens the development cycle.

I do sometimes find RStudio to get stuck and slow when the code became long, so that is a place for enhancement.
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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 the production and consumption of knowledge by everyone, regardless of economic means.

Their commercial software products, including RStudio Server Pro, 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

Has featureConnect to Multiple Data Sources
Has featureExtend Existing Data Sources
Has featureAutomatic Data Format Detection

Data Exploration Features

Has featureVisualization
Has featureInteractive Data Analysis

Data Preparation Features

Has featureInteractive Data Cleaning and Enrichment
Has featureData Transformations

Platform Data Modeling Features

Has featureMultiple Model Development Languages and Tools
Has featureSingle platform for multiple model development
Has featureSelf-Service Model Delivery

Model Deployment Features

Has featureFlexible Model Publishing Options
Has featureSecurity, Governance, and Cost Controls
Additional Features
Has featureShare Data Science insights in the form of Shiny applications, R Markdown reports, Plumber APIs, dashboards, Jupyter Notebooks, interactive Python content, and more.

RStudio Screenshots

RStudio Videos (2)

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

Jupyter Notebook, Streamlit, Kubernetes, Apache Spark, Databricks Unified Analytics Platform, bokeh, Slurm, Dash applications, VS Code, SAML Marketplaces

RStudio Competitors

RStudio Pricing

  • Has featureFree Trial Available?Yes
  • Has featureFree or Freemium Version Available?Yes
  • Does not have featurePremium Consulting/Integration Services Available?No
  • Entry-level set up fee?Optional

For an overview of our pricing philosophy, please see https://rstudio.com/pricing/approach/. For pricing options for RStudio Cloud, please see https://rstudio.cloud/plans/free. For consulting and integration services, we work with our Certified Partners: https://rstudio.com/certified-partners/.

RStudio Support Options

 Free VersionPaid Version
Forum/Community
FAQ/Knowledgebase
Social Media
Video Tutorials / Webinar
Email

RStudio Technical Details

Deployment Types:On-premise, SaaS
Operating Systems: Windows, Linux, Mac
Mobile Application:No