TrustRadius Insights
Intuitive User Interface: Users have found RStudio to have an intuitive user interface that allows them to quickly test and debug code. …
Overview
What is Posit?
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
Recent Reviews
Awards
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Popular Features
- Visualization (26)8.484%
- Connect to Multiple Data Sources (25)8.181%
- Extend Existing Data Sources (26)7.474%
- Automatic Data Format Detection (25)6.363%
Reviewer Pros & Cons
Video Reviews
2 videos
RStudio Review: It Proves To Be A Reliable Statistical Tool W/ Support Avenues In Place If Needed
02:53
RStudio Review: Works As An Useful Tool But User Finds Free Version Could Be More Competitive
02:13
Pricing
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What is Posit?
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
Entry-level set up fee?
- Setup fee optional
For the latest information on pricing, visithttps://posit.co/pricing
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- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Demos
What is Posit Workbench? Build Data Products in R & Python using Jupyter, VSCode, and RStudio.
YouTube
Posit Connect | Host all of the data products you create
YouTube
Features
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Product Details
- About
- Integrations
- Competitors
- Tech Details
- FAQs
What is Posit?
Posit, formerly RStudio, provides a modular data science platform that combines open-source and commercial products.
their open source offerings, such as the RStudio IDE, Shiny Server, rmarkdown and the many packages in the tidyverse, boast users among data scientists around the world to enhance the production and consumption of knowledge by everyone, regardless of economic means.
Their commercial software products, including Posit Workbench, Posit Connect, and Posit Package Manager, are available as a bundle in Posit 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 Posit 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.
Posit’s open-source software and commercial software form what the vendor describes as a virtuous cycle: The adoption of open-source data science software at scale in organizations creates demand for Posit’s commercial software; and the revenue from commercial software, in turn, enables deeper investment in the open-source software that benefits everyone.
Posit 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, Quarto content, R Markdown reports, Plumber APIs, dashboards, Jupyter Notebooks, and interactive Python content.
Posit Screenshots
Posit Videos
Open Source Software for Data Science - CEO J.J. Allaire provides an overview of Posit's mission, and why Posit has become a Public Benefits Corporation.
Posit Integrations
- Amazon SageMaker
- Kubernetes
- Apache Spark
- Jupyter Notebook
- Streamlit
- Tableau Desktop
- Azure Machine Learning
- Databricks Lakehouse Platform
- Microsoft Visual Studio Code
- Bokeh
- Slurm
- Dash applications
- SAML Marketplaces
Posit Competitors
Posit Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Windows, Linux, Mac |
| Mobile Application | No |
Frequently Asked Questions
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
Reviewers rate Security, Governance, and Cost Controls highest, with a score of 8.9.
The most common users of Posit are from Enterprises (1,001+ employees).
Comparisons
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Reviews and Ratings
(237)
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Pros
- Cons
- Recommendations
Intuitive User Interface: Users have found RStudio to have an intuitive user interface that allows them to quickly test and debug code. This has been mentioned by numerous reviewers, highlighting the ease of use and convenience it offers in coding tasks.
Seamless Integration with Git: The seamless integration of RStudio with Git has been praised by users, making it easy for them to manage version control. Several reviewers have specifically mentioned this as a major advantage of using RStudio for their coding projects.
Powerful Statistical Analysis Tool: Many users appreciate RStudio's capabilities as a powerful tool for statistical analysis and data exploration. They mention its ability to import data from multiple sources, apply machine learning models easily, and export data into various channels.
Confusing and Outdated User Interface: Several users have expressed dissatisfaction with the user interface of RStudio, finding it confusing, unattractive, and outdated compared to other tools. They feel that the interface is too technical for business people.
Frequent Crashes with Large Datasets: Some users have mentioned that RStudio frequently crashes when loading large amounts of data. This can be frustrating and disrupt their workflow.
Lack of Integration with Other Applications: Users have pointed out that RStudio is not as integrated with other applications as Python. This limitation makes it less convenient for users who rely on seamless integration between different software tools.
Users commonly recommend RStudio for beginners in R programming and data analytics. They believe that RStudio is a good tool for learning machine learning and recommend using it for data work, programming R code for machine learning, implementing R software, data analysis, and data science. Users consider RStudio to be a great resource for analyzing data and necessary for anyone who wants to get into R programming. While considering other suites and languages like Python, they still recommend taking a look at RStudio for data analysis. Additionally, users find RStudio to be useful for doing statistics and creating professional plots and figures. They suggest familiarizing oneself with common libraries in the field and doing online tutorials before starting to use RStudio. Users warn about the steep learning curve but believe it is worth investing the time to learn it. Moreover, they recommend using RStudio for big data and epidemiological research.
Attribute Ratings
Reviews
(76-100 of 122)Companies can't remove reviews or game the system. Here's why
December 12, 2020
RStudio Can Simply Your Life
We use RStudio as an analytical platform for building models, testing them, and sharing the results with others. We also use it to build Shiny apps and are shared with other users. At the moment, it's primarily used by technical users who have a background in modeling. But we also use it to access, transform, and prepare data that will be used in modeling or reporting use cases.
- RStudio does an excellent job providing a clean user interface for R or Shiny applications
- RStudio integrates natively with version control software
- Users can program with either R or Python
- RStudio has a command line built in, eliminating the need for a separate program for a REPL
- The integration with Packrat is confusing at first
- If you don't create a project, it's easy to accidentally modify the default workspace
December 12, 2020
Nice IDE that keeps improving
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.
December 11, 2020
RStudio--A go-to for data science teams
RStudio is primarily used by the data science team in my organization to analyze client data, create interactive Shiny apps for our clients, and much more. We also use it to develop internal R packages for our company's data science tool box.
- Customer service
- Well-documented product
- Very flexible--can meet just about any business need
- More tutorials on the more complex things it can do.
December 11, 2020
RStudio is a great IDE
RStudio is used by the department. It is used from exploratory data analysis to whole research and development projects. Although its applicability mostly focuses on data exploration, more and more teams are starting to realize the many advantages that it can bring into other areas, that it can go from model training to production.
- Data wrangling
- Data visualization
- Machine learning
- Deep Learning
- Unified machine learning framework
December 11, 2020
Commercializing Analytics Products using RStudio
RStudios products are at the core of all of our solutions and utilized across our entire organization.
In addition to supporting all research and development of solutions, we utilize the RStudio Connect service to disseminate all of our customer facing solutions.
Between RStudio Connect, RStudio Package Manager, the RStudio IDE - suffice it to say our company would not function without RStudio's products. We've grown with RStudio since they first released the IDE and Shiny and are proud early adopters of their solutions. Having the flexibility to leverage our R expertise and turn this into enterprise software solutions was a game changer.
In addition to supporting all research and development of solutions, we utilize the RStudio Connect service to disseminate all of our customer facing solutions.
Between RStudio Connect, RStudio Package Manager, the RStudio IDE - suffice it to say our company would not function without RStudio's products. We've grown with RStudio since they first released the IDE and Shiny and are proud early adopters of their solutions. Having the flexibility to leverage our R expertise and turn this into enterprise software solutions was a game changer.
- Maintains a suite of software services that allows you to build enterprise analytics solutions.
- Supports the R community by maintaining excellent packages.
- Has tremendously detailed sources of documentation for all their products and services.
- Strong technical customer support.
- We tend to push the boundaries of what one can do with RStudio's services. Sometimes we are ahead of the curve and have to custom build solutions that RStudio has not addressed in their core product offerings.
- Archive documentation and consistently redirect to newest documentation.
It is being used across my organization. In general, it addresses the problem of selecting an IDE for the development of R scripts. For my group, use of RStudio Server and RSConnect addresses the problem of collaboratively developing and deploying R Shiny apps.
- Generally great IDE for R script development.
- Has functionality tailored to useful R packages, e.g. streamlined shiny app deployment.
- Integration with GitBash terminal is really helpful.
- Stability: sometimes crashes unexpectedly.
- Moving script tabs around is clunky.
- Documentation about all of its great functionality could be improved.
December 08, 2020
Teaching with RStudio Cloud
We used RStudio Cloud to introduce students to coding in R and statistical computing. The class, "Visualizing Society," is typically in person, but because of COVID we had to transition to online learning. RStudio Cloud allowed us to avoid installation and dependency issues for our students, often the most challenging problems for individuals new to coding. Every student would just log into RStudio Cloud and have the materials they needed for the day.
- RStudio Cloud allows instructors to have control over the materials and RStudio setup students are working with.
- RStudio Cloud also gives instructors instant access to student materials so that they can check progress and see where students are stuck.
- RStudio Cloud is a very clean and easy-to-navigate interface for students and instructors.
- The biggest missing functionality, which I know RStudio is working on, is allowing Google Doc-style multiple editors per project. This would really enhance the opportunities for peer collaborations.
- Relatedly, it would also be helpful if instructors could update project materials after students have already cloned a project. There were multiple times when students would clone a project and it would be brought to my attention that one piece of information was missing. The only solution at the time was to go into each student's project individually, but this was very time consuming.
December 07, 2020
RStudio Solved Our Data Science Pipeline
RStudio is being used both within my department and across the entire enterprise to support analysts in their roles. Analysts conduct research, support studies, and drive data viz for higher up stakeholders.
- Code accessibility and streamlining.
- Publication and hosting.
- Collaboration between users.
- Error reporting innate to base R.
- Interaction with other IDEs.
- Internal rendering of HTML reports before export render.
December 07, 2020
Data science at its best
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.
December 07, 2020
RStudio is the best way to use R
We use RStudio to implement code-based actuarial analysis. We use this is several offices across our practice. It provides a tool to facilitate our execution of R cade.
- Excellent IDE.
- Type ahead and in-line help.
- R package management.
- The git feature is slow.
- Options for code highlighting.
December 04, 2020
RStudio Enables Computational Biology At Scale
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)
December 04, 2020
Cool RStudio experience
We are using RStudio Connect to share data, on-the-fly data analysis and data visualization across the whole organization. This server provides comprehensive data analytical capabilities to lab scientists and clinical trial scientists to visualize and interpret preclinical and clinical data. We found RStudio to be a great platform to support this goal.
- Facilitate comprehensive data analyses
- Very nice visualization capabilities
- Not much IT workload to manage the RStudio server
- Easier integration with Python
- More flexible interface
December 04, 2020
RStudio and RConnect
We use RStudio for data analysis and visualisation. RStduio Connect is our go-to platform for publishing dashboards and reports.
- Collaborative work
- Simple to use interface
- Ease of publishing outputs to the web
- Data visualisation
- Package version selection
December 04, 2020
Great enterprise solution!
It is used by the Data Science team for all projects. Internal Shiny apps are deployed on Connect, which are used by other teams as well.
- Easy Github integration is key to nudging all to use version control.
- Seamless support for Python users as well has been a lifesaver!
- Customer support has been dedicated, responsive, and informative.
- The engineers who were installing were missing certain documentation needed.
December 04, 2020
Satisfaction with RStudio
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
December 04, 2020
Excellent suite for data science!
We use the suite of RStudio products within our (small) team but we serve a larger department. We address different kinds of business. We use RStudio Package Manager to distribute the code produced by expert programmers as R packages; we use RStudio Server Pro to develop the code of R packages, scripts and shiny apps; we use RStudio Connect to distribute shiny apps to colleagues of other departments.
- Simultaneous management of programming environment for different sessions.
- Code management via git.
- Deployment of shiny apps.
- Management of different versions of packages, especially from bioconductor.
- Better integration with bioconductor.
- RStudio Connect on Windows.
- Dashboard of app usage (by different users) for RStudio Connect.
December 03, 2020
RStudio is the best!
RStudio is used in the organization for building machine learning models based on R language as well as building user interfaces for marketing analytics using R Shiny framework. The machine learning models help understand customer needs and behaviors which drives personalization. Marketers then access this information using an intuitive user interface (based on R Shiny) to take data-driven decisions.
- Great IDE for development.
- Open source options allows individual users to learn and develop.
- R Shiny is a great tool to build intuitive data applications.
- Observing some crashes in the latest version.
December 03, 2020
Boost your collaborative work
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.
December 02, 2020
RStudio Rocks!
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
December 02, 2020
System Administrator's view on RStudio
RStudio is being used by our research analysts to perform statistical probabilities of different treatments for end-stage renal disease in America to find out who is more likely to suffer from this disease and what are statistically the best treatment avenues available for dialysis patients. RStudio is used by approximately 15 analysts to perform these studies.
- Flexability
- Package update
- Community support
- Documentation
- Better packaging of dependencies for packages regarding the Linux OS being used
- More support for mixed OS environments
- RStudio Server Professional installation support for Windows OS
November 24, 2020
RStudio enables us to do more, more easily
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.
November 24, 2020
Rstudio IDE - The Gold Standard
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
March 30, 2020
Good tool for statistical data scientists
Score 9 out of 10
Vetted Review
Verified User
Since my company is a large financial institution, tools used with some groups might not be shared with other groups and some tools used in some geographical locations might not be used in other locations. R and Rstudio is such a tool. RStudio is basically the default option if you are using R.
- Easy.
- Clear.
- Free.
- No multi-language.
- Version control is hard.
- Manage environment.
February 25, 2020
Rstudio statistician's best friend
I have used RStudio for various data analysis at my company from data cleaning to data visualization and model selection. The entire organization widely uses RStudio. RStudio helps in ad-hoc analysis and enables users to run line by line and easily create R markdown files as well as a shiny app.
- Stats best tool
- Easy exploration data analysis
- Package building
- Package version selection
January 28, 2020
The open source alternative to Matlab
RStudio is used as a free, open-source alternative to MATLAB. We can generate custom codes to solve a variety of data analysis problems. These scripts can be easily shared with other users with little hassle in trying to purchase additional software.
- Easy to learn language
- Clean UI for R software