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Posit

Posit
Formerly RStudio

Overview

What is Posit?

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

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Recent Reviews

TrustRadius Insights

Intuitive User Interface: Users have found RStudio to have an intuitive user interface that allows them to quickly test and debug code. …
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All-in with RStudio

10 out of 10
June 30, 2023
Incentivized
RStudio products are used across multiple departments in our organization, including the research, IT, and data science business units. …
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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 (26)
    8.4
    84%
  • Connect to Multiple Data Sources (25)
    8.1
    81%
  • Extend Existing Data Sources (26)
    7.5
    75%
  • Automatic Data Format Detection (25)
    6.4
    64%

Reviewer Pros & Cons

View all 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
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Pricing

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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
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Features

Platform Connectivity

Ability to connect to a wide variety of data sources

7.3
Avg 8.5

Data Exploration

Ability to explore data and develop insights

8.3
Avg 8.4

Data Preparation

Ability to prepare data for analysis

8.2
Avg 8.2

Platform Data Modeling

Building predictive data models

8.2
Avg 8.5

Model Deployment

Tools for deploying models into production

8.6
Avg 8.6
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Product Details

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

Screenshot of Posit runs on most desktops or on a server and accessed over the webScreenshot of Posit supports authoring HTML, PDF, Word Documents, and slide showsScreenshot of Posit 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 Posit Workbench within various systems such as Kubernetes and SLURM with Launcher.Screenshot of Jupyter: Author and edit Python code with Jupyter using the same Posit Workbench infrastructure.Screenshot of Posit Connect enables users to deploy Interactive Python Applications (including Dash, Bokeh and Streamlit), in the same place Shiny apps are shared.

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.

Watch Overview of Posit Connect

Posit Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo

Frequently Asked Questions

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

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

Reviewers rate Security, Governance, and Cost Controls highest, with a score of 8.8.

The most common users of Posit are from Enterprises (1,001+ employees).
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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!

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

(1-25 of 122)
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Samrit Pramanik | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
I will highly recommend Posit to anyone who works in Advanced analytics because of its high computing power and seamless delivery of model output of various analytical case studies and problems.

Based on my experience, I use Posit software aka RStudio Pro and Posit Workbench for almost everything in our company as well as clients network. From data preparation to statistical and predictive model building, I use RStudio Pro exclusively. In addition to this, data visualization and data manipulation are also done by Posit software.
I have used multiple R packages for various kind of data analysis from logistic regression, classification to LASSO and elasso (Network Analysis).

Only one scenario I would like to say that it is less appropriate is to view the data of formats other than data frame. I really wish to see this issue will be solved in the next major updates of Posit.

Overall Posit is really a good software and platform for any kind of data analysis and visualizations. Thanks.
June 30, 2023

All-in with RStudio

Score 10 out of 10
Vetted Review
Verified User
Incentivized
RStudio is the only feature-rich R IDE in the industry, so for the majority of our work, we will use the IDE. There are times when we deploy our scripts outside of the IDE. A recent example was when we had a large amount of data that was too much for the IDE itself. We used the IDE to write a script and then deployed that script outside of the IDE to multiple servers. It would be helpful if we could run a single script across multiple servers based on defined partition.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
Posit is well-suited to just about any scenario you can throw at it. Basic data manipulation, statistical analysis, visualizations, machine learning, simulation - there is a function or library out there for everything. It's also lightning fast, which is a blessing when computing large calculations. Less well-suited to Posit is its learning curve - syntax is relatively unique and picking up a new package usually means learning new behaviours.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
RStudio is well suited for professionals who need to interpret and analyze large sets of data. It can have a step-learning curve though so maybe less functional and not appropriate for an inexperienced user. Additionally, if users are trying to collaborate on a set of data, additional programs or software may be needed in addition to RStudio in order to collaborate.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
RStudio is appropriate to perform complex analysis and data modeling exercises while is not that useful where the analysis is simple due to complexity where Excel will better suit. Also, if your organization is not used to it, probably, is better to use other software. Any kind of statistical analysis like regressions or decision trees would be a very good option to model with R Studio.
Akshat Garg | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
RStudio is well suited for data processing and visualization. The tool provided a very interactive and user-friendly environment to understand each step in the data processing. However, RStudio lacks in adoption among the data science community as python is not available and most of the machine learning libraries are custom built for python.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
well suited: creating and delivering apps for multi-disciplinary teams, for example, http://drugis.org/index or https://shiny.rstudio.com/gallery/covid19-tracker.html less appropriate: Kaggle competitions, multi-community collaborations, Google collab...scenarios when the whole communities decide to work on a specific problem in Python and R is left behind, e.g. in 2015 my colleague delivered better results with Bayesian statistics simply cause he decided to go for Python to visualize joint distributions (priors and posteriors) ...even if I had way more knowledge on the algorithmic side, I was simply slower because I chose R; what I have learned over the years is that when it comes to the stakeholders, a good visualization (==communicating the results and effectively advertising) is everything as without it there is no funding and without funding no science, no R&D
Score 10 out of 10
Vetted Review
Verified User
Incentivized
Any analytical problems that start with data could be tackled with R in an agile and flexible manner, and since RStudio does such a good job of embedding R to the product itself, it is great for industries/companies with such problems.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Based on my experience, I would like to recommend RStudio to anyone that needs to run small to medium-sized statistical analysis quickly and cost-effectively. Many packages are written pretty friendly for producing readable output for regressions results. However, it is less suited to large-scale big data projects that require large processing power.
Score 6 out of 10
Vetted Review
Verified User
Incentivized
RStudio is the best option I've seen for data cleaning, prep, and transformation. Other tools, such as Tableau or Excel, are not easily transferrable to other formats or are manual and take too much time. RStudio is less appropriate for small datasets and academic courses that won't dedicate as much time to learning the fundamentals of R.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
RStudio is the best studio for statistical analysis, reporting with graphs and charts, or building custom dashboards that would refresh the data from backend tables at a set frequency. It's good for data visualization, data modeling, and data visualization. I have limited experience in machine learning using R (I have mostly been using other software), so I cannot comment on its capabilities for that.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition.

A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
RStudio is well suited, particularly to providing an environment for the statistical analysis of datasets and leveraging various data analysis packages using R. Its user interface is highly customizable and provides all the information users need to script, run, and generate various GUIs and dashboards. Overall it's well suited to R and perhaps less well suited (although it does allow) for other languages such as Python. Overall it's well suited for analysis needs but probably less suited for other development needs, especially if they require the heavy use of other languages.
Jim Gruman | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
RStudio is the premier statistical workbench and development environment for professionals. It is well suited for serious data science and statistical analysis on local compute hardware and in the cloud. RStudio is not a graphical toy.
Kunal Sonalkar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
RStudio is very well suited for data analysts and statisticians. Writing and designing predictive data models is very efficient and there is a lot of online help if you plan to use standard machine learning algorithms like Naive Bayesian, Apriori Analysis, Random Forest, DENCLUE,, etc.

In a situation where you want to automate excel reports then shiny (user interface for R) comes in very handy.
Suryaprakash Mishra | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
RStudio is very easy to learn and learn. Lots of free resources and user groups and support is around to enhance individual capacity to solve problems. Most recently we used RStudio to geospatially map road infrastructure within 100 meters of crashes in Victoria.
Chris Beeley | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
If you've got a bit of Linux skills in your organisation, and if you have the money to pay for RStudio Connect (or RStudio Workbench on the development side) then I think RStudio is definitely a sound investment. If you don't have Linux skills, or your analysts are not sufficiently advanced in R to need to deploy stuff running live (and are just emailing stuff around, basically) then you're probably not ready yet.
Kenton Woods | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
I would use RStudio if you need a cheap way to effectively analyze data using social network analyses. Linear regressions are also fairly easy to run in RStudio, but if you have the money I'd recommend going another direction for your statistics needs.
Bobbi Woods | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
RStudio is perfect for statisticians who want to run descriptive and predictive analyses but do not want to spend big money to acquire a license from a competing statistics software. It is less suited for scenarios in which a company will reimburse for a license, in which I would recommend IBM's SPSS over Rstudio.
January 20, 2022

Hooray RStudio.

Score 8 out of 10
Vetted Review
Verified User
Incentivized
There are tons of examples which we feel great when we have RStudio. At whole, I extremely enjoy how RStudio encourages/brings update to the community. There are just lots of great packages coming to CRAN, which are easily accessible and loadable from RStudio.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
I would definitely recommend RStudio for business analytics. The interface is extremely user-friendly and intuitive. There are a wide array of inbuilt functions and limitless packages available to support almost any analysis desired. The only caveat is processing tends to be slow for datasets larger than about 2 GB.
January 18, 2022

RStudio is wonderful!

Score 9 out of 10
Vetted Review
Verified User
Incentivized
I really like that RStudio has the ability to run code line by line. That is crucial in my work as I am constantly modifying and testing little things that would not be practical/desired to run the whole code.
Prashast Vaish | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
It's is best suited for data cleaning and analytics. It is an awesome tool if you want to apply some statistics operations. It can handle large amounts of data It is not the best tool if you want to start with coding in general as concepts are a little tough.
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