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)6.464%
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
N/A
Unavailable
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
Offerings
- 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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(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
(1-3 of 3)Companies can't remove reviews or game the system. Here's why
January 26, 2022
Enhancing Data science capabilities with RStudio
I have extensively used RStudio, when I was seconded to the Department of Health in Victoria to assist with the surge in COVID19 Delta response. In my day to day, I used R mostly for Descriptive and Graphical analysis and data management. Most of the analysis is used to provide insights to reduce road trauma and promote road safety.
- 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.
100%
10.0
100%
10.0
100%
10.0
100%
10.0
100%
10.0
- Much cheaper option then SAS.
- Data science and machine learning- used to solve complex business problems.
- Enables to launch Data Science project in Cloud-based environment.
Amazon QuickSight, Power bi, SAS EG, Tableau, Salesforce (TREVI) - Victoria, SharePoint.
6
Data Science team within Business Intelligence team
2
Our technical and installation is managed by the ITSS shared services.
- mapping of crash data to road asset data
- deep dive to find out more about crash data to support road safety
- Text analytics of the survey data and meeting notes were collected from all the council visits in Victoria.
- The Data Science team extensively used R for Injury coding
- mapping of crash location and road infrastructure data
- May be more across analytical teams with bit of training
- Mostly all packages
- data management and data cleaning
- graphical representation
- Data science and statistical analysis
- none, however, this depends on the problem/issue that we are trying to resolve.
- This also depends on the experience of the user and support available around if there is something not directly available on web.
Yes
I just tried RStido with my Android Mobile and it runs well without any issue.
September 06, 2021
RStudio for quick prediction prototyping
Very few of us are getting into predictions using Machine Learning and Data Science. We use Rstudio to program our algorithms. There are only a handful of people in the whole organization who use Rstudio right now. We use it in pockets, and do the proof of concepts with Machine Learning using R.
- We use it for a quick visual representation of data
- We do exploratory data analysis to understand data
- We do predictions using RStudio
- When we have to run 100 iterations using more than 10000 records, RStudio gets stuck or takes a very very long time to respond
- Generating a pdf report from an RMD file is very difficult from RStudio.
- Generating a pdf report in RStudio cloud is straightforward and inbuilt.
- RStudio is free and it's easy to start using it
- It's easy to install new libraries and start using them seamlessly
- The installation of some libraries is challenging, especially when they depend on a lot of other libraries.
- RStudio crashes when there is a clash between libraries somehow.
I have used Jupyter notebooks. I have used the cloud version of RStudio extensively. I program mainly in R as we have some libraries on Microstrategy which are in R. So, R was a natural choice for prototyping. I also use Jupiter Notebook for python programming. But, I use this less often than R.
10
We are a varied group of individuals coming from different backgrounds. Some are data scientists, some are Ph.D. doctors, some are programmers like me. All of us work on business problems, which present a lot of data which does not have immediate meaning to the business. We try to run predictions based on that data.
10
We are a bunch of programmers who use Rstudio. We do not really support the software, but we use it. We do help each other when we run into issues or get stuck into specific programming needs using R. Most of us have some kind of programming experience. There are some Ph.D. scientists who also program on RStudio.
- Running quick predictions based on the data at hand
- Representing data using graphs and charts
- Exploratory data analysis using RStudio
- We use it for scatterplot matrices
- We use it to quickly see the dependencies of various predictors
- We check multicollinearity between our input columns
- We hope to use it on a production run basis on cloud
- We need to be able to scale our prototype solution to larger sets of data
- We wish to have stable models, using Rstudio, which can be dynamic based on new data
No
- Price
- Vendor Reputation
- Third-party Reviews
It's free and easy to use. That's most important, as it gives us the flexibility to switch to something else for our prototyping needs.
If we had to do it again, we would like consider a product which is cloud first. We currently use RStudio Cloud, which is close to what we want in the future. But how much can we scale is the question. We have not really tested that yet. We would assume there are options to use it on cloud vendors such as Azure and AWS.
- Implemented in-house
No
Change management was minimal
I did not purchase premium support. I just use the cloud-based and RStudio IDE.
No
None
- Generation of HTML reports out of the RMD
- quick help files for any functions
- A quick view of data files
- The loading of files with lot of data takes a lot of time
- Generation of pdf report from RMD is not very easy.
No
February 12, 2018
RStudio as a documentation tool for software development
We are software developers, not data scientists. We use RStudio for documentation. The .RMD pages allow us to document operational and development tasks with repeatable commands and/or scripts intermixed with explanations.
- Document BASH and build scripts written in various languages.
- Run Ad Hoc and initial SQL statements against our databases.
- Easily publish the .RMD documents as HTML or PDF files.
- Support for NodeJS and Javascript.
- Better examples and documentation regarding PanDoc.
- Saves us time when communicating complex setup procedures.
VSCode is our primary code editor. It also supports Markdown. If fact it has real time rendering of Markdown and HTML in side by side panes. While it has an excellent debugger, it does not have executable statement intermixed with descriptive test.
- Mixing executable code with text explanations
- Generating and publishing HTML and PDF files from Markdown documentation
- There is no debugger. Support of BASH command is difficult.