Posit

Posit
Formerly RStudio

Customer Verified
Top Rated
Score 8.7 out of 10
Top Rated
Posit

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

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How Posit Differs From Its Competitors

Open Source

We choose open source because it is free, well documented, has lots of existing support available (eg: StackOverflow) and is (usually) up-to-date. Open source data science is always going to move very quickly due to its collaborative nature, ensuring we always have access to the latest methods and …
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Customer Support

RStudio online support is fantastic. In addition to their online support, there are tons of different platforms on the web for people to ask for help, troubleshoot, and work with other RStudio users when they run into a problem.
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Open Source

Open source data science allows us to share our code and process with multiple users. This is especially helpful when publishing papers that we want to be shared with as large of an audience as possible. It makes our work replicable and reproducible, which is very important to the field of …
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Open Source

We think the open source version is good enough for the task we are currently doing. R Studio open source offerings are very complete and only in some cases would be necessary other packages.
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Customer Support

my very personal opinion: regarding validated statistical documentation I trust, SAS is the winner, then Stata however, RStudio is the winner to me when it comes to dedicated Customer Success representatives
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Open Source

1. it does not discriminate against creative minds based on their financial status 2. it is easier to create a pilot tool to show to the stakeholders/customers first, before requesting any funding 3. it is a more reliable, convenient way of running the business, as not linking the access to …
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Professional Offerings

I have one comment: these are great tools, but some of these solutions are very expensive, very often hard to justify the spending at the beginning stages of the work, without the proof of principle
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Hosted Offerings

I think shinyapps.io improves communication, especially through interactive visualization. In my job I am often expected to make very complex, abstract ideas (that take many years to fully understand or develop) simple and "communicable" to the non-technical audiences within minutes (literally, …
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Customer Support

RStudio provides technical support with a ticket system. So far 80% of the issues encountered have been resolved by back-and-forth written communication which usually starts with running a diagnostic report, and ends up consuming a significant chunk of time for both parties; the rest can be …
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Open Source

Open source means easy collaboration and interaction with people who invest much time and energy developing the tools, which then provides a sense of reliability and trust when using the tool. It also provides an opportunity to participate in the process of developing a better tool with a …
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Professional Offerings

RStudio Server Pro provides the workstation for a data scientist to create analytics, which then is curated to content/tools on RStudio Connect that helps the business audience understand a certain business problem better. To be able to reproduce the content, the analytical environment needs to be …
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Customer Support

I don't really have experience using customer success support from RStudio before. Still, I have used the documentation provided for R Shiny, which I found pretty useful when developing interactive visualization. I felt other tools like Plotly for Python had better documentation, so RStudio could …
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Open Source

There are many resources out there for open sources packages, and it is free to use. The good thing about open source in data science is transparency and flexibility. We can see how the packages are written so we know the underlying assumptions in the models and how we can customize them for our …
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Customer Support

I have not used their online documentation, email support, and Customer Success representatives. There are times I wish I had that support; however, I was not aware that was an option for users. I would have wanted those customer support options to be more visible or communicated while I was …
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Open Source

I believe I use RStudio's open-source offerings, though I'm not entirely sure. I use libraries, such as ggplot, which I have found from Googling my question. I mostly use these tools to streamline the data analysis process, which helps me explore the tool and complete my project goals efficiently.
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Open Source

We don't use Shiny at the moment since all the front-end visualization is based on the Tableau platform. The main reason for using RStudio was the cost to performance ratio. Believe me, when your denominator has 'free' in it, and the quality of the product is not sub-prime, you've got a great …
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Customer Support

I haven't really used RStudio support but participated in some workshops around shiny and tidyverse, which were both extremely clear, enjoyable, and well-executed - our organization learned a lot from them, so I would highly recommend them.
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Open Source

The open-source offerings are well maintained. They offer a set of functionalities that would be difficult or time-consuming to implement on an individual basis, so they offer us major time savings. The main advantage I see in open source data science is that it'll reduce duplicate work and enable …
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Professional Offerings

We've only used RStudio connect minimally, and so far, it has helped with onboarding other groups that are less familiar with RStudio and R in general. Using Rstudio connect was also super helpful for use in training sessions in general.
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Hosted Offerings

Shinyapps.io has been really helpful in hosting interactive data GUIs for users/consumers of our data analytics in the form of a separate user interface that is easier to understand, and it allows users who are less comfortable with R to use to view and consume the analyzed data in a consistent way.
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Customer Support

Unfortunately, there was no need for me to contact customer support. I have received excellent training from senior colleagues and hands-on experience and shadowing when they were building codebase.
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Open Source

I have not used Shiny in my current role, however, one of our analytical providers used shiny to analyse and visualize road crash data.
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Collaboration

Rstudio helped me during my secondment with the the Victorian Department of Health to assist with the COVID-19 data management and reporting. We used RStudio through VM.
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Data Science and BI

I use Tableau for dashboard and used RStudio to create pipeline workflow. I used this for updating the power bi and Tableau for reporting of COVID-19 cases.
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Support for Python

I do not have much experience and knowledge of Python at this point in time neither at the Department of Health or with my current organisation.
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Customer Support

I mentioned this in my bullet point list of what they do well. RStudio customer support is absolutely first-rate, they have Linux, Python, and R experts and they are extremely professional and helpful. I gather they even escalate problems they can't solve to engineering so a fix or workaround can …
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Open Source

I work in publicly funded healthcare and open source is a vital tool to allow us to do complex work cheaply. We use open source because it's cheaper and better and we publish our own source code and contribute to open source repositories because it's the right thing to do and it improves the space …
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Professional Offerings

We use RStudio Connect and it offers one-click publishing. My least techy analyst can deploy stuff and get it out to decision-makers with minimal support and training for me. It does version control of packages in R and Python, which is pretty much essential, it can be used to deploy HTML/ …
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Collaboration

RStudio is vital to what we do. We run R and Python models in production and deliver them to multiple organisations. It's the only platform that I would consider for code first data science, and RStudio Connect makes publishing really easy for individuals who don't understand Linux and networking. …
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Data Science and BI

We haven't explored this too much yet. We do plan to weave together some of our R outputs with some PowerBI outputs, but this is not simple just because we don't have users who are expert in both platforms. Ultimately we are going to need to join the two together and I'm reasonably confident that …
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Support for Python

We using Python with reticulate to feed NLP analyses done in Python to an R/ Shiny powered dashboard. We don't currently use it for Python on its own. To be honest I don't highly rate the dashboard/ reporting facilities in Python so it's no great loss at the moment but we certainly have it on our …
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Collaboration

It has helped me share business insights across the organization. I use RStudio to present statistical analyses that benefit other researchers in our department and their own professional goals. RStudio helps me convey statistical analyses in a variety of visual possibilities that make it easier …
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Data Science and BI

I have indeed used RStudio in conjunction with Tableau. Tableau has allowed us to create a variety of visualizations for our data to more easily convey our results to a lay population. It's a very important piece in our translational work. In essence, we pull in our data and run analyses in …
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Open Source

I have primarily used RSiena, which is an advanced social network analysis package. I think the value in open source data science is, other than the very low cost, the availability of learning resources to users who hit a roadblock. Being able to search the internet for solutions to common issues …
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Open Source

Shiny is a great tool, and it provides an easy approach to develop a dashboard without much web developing experience. I absolutely love the open source community since people are consistently throw new ideas and provide feedbacks as well. That's how things can get better. Love it!
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Professional Offerings

RStudio Connect is such a great platform with lots of flexibility, although we are currently using a small chunk of them. It supports us to delivery insights to our internal team members as well as some external user outside organizations. RSPM is also great since it's a headache to handle private …
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Open Source

Yes, I have used various open-source R tools. Open-source data science is advantageous as people can contribute to its growth freely and is not centralized by a company. Even students.
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Professional Offerings

I have used the R server in particular. It is extremely good and pretty fast. It allows multiple users to use the tool at the same time. It can be easily connected to a git repo and processes can be automated.
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Open Source

I use rayshader as my primary package for creating maps and it is remarkable. It is beyond easy to create any 3D map terrain or develop 3D maps from existing topographic or geologic maps to make the experience easier to read and understand for the customers that we work with.
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Open Source

I love open source because I like things being free and open to those who can develop and release packages that help the entire community.
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Customer Support

Quick to respond and usually resolves problems within a week.

At times, the support team is willing to go beyond regular service agreements to help customers resolve the issue - e.g., internal code bug - and this not often seen with other vendors.

RStudio team also develops may useful open-source …
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Open Source

It allows for grassroots movement and demonstrate the value of analytics products, built on open-source software, to management prior to investing on commercial version.

We were able to grow the community of developers and users internally and boost data and programming literacy for non-coders, …
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Professional Offerings

Not having to manage resources required to run apps for multi users and being able to integrate the development IDE with publication platform is a plus. To build a similar infrastructure internally would've cost more and likely not as well integrated as RStudio Teams.
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Hosted Offerings

RStudio generously offered RSPM (package manager), which offers binary installation for Linux-based OS, and this really helps with quicker project start-up.
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Python

RStudio offers integration with popular IDEs - e.g., VS Code and Jupyter - and leverages the existing publishing workflow that is user-friendly and robust.

This allows minimal friction and overhead for Python users to adopt the platform.
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Customer Support

There is no customer support available for RStudio. All online documentation is user-based. You can search Cran, Github, Reddit, StackExchange, and more for answers. One of the best sources for learning the program is to look up the type of analysis you are wanting to perform. Many data scientists …
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Open Source

I use RStudio, which is the IDE of R. RStudio primarily acts as a much more modern and user-friendly platform. With the four major panels (environment, plot, console, and script) easily laid out so that you can check all the information for your analysis easily and quickly. I also use a variety of …
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Customer Support

The online support documentation was excellent, and we benefitted from direct support from the r-studio technical team to help answer our questions and to ensure that our infrastructure was set up to scale to the users that we expect. We have had a good experience so far so we are hopeful this …
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Open Source

Being a large corporate company we were not eligible for using the open source version of this software suite. However, there is huge value in the open source data science community as a whole. Chances are that there is a team or developer out there who has released a package that contains a …
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Professional Offerings

Each of the 3 products - Server Pro, Connect and Package Manager, are a separate piece of the puzzle.

- Server Pro gives the developers access to a shared IDE, accessible via the browser
- Package Manager offers a simple way to publish and consume common packages and
- Connect allows you to publish …
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Hosted Offerings

We are not using the above apps, this is currently a private, internal installation. To satisfy InfoSec we needed a non-cloud solution that could be backed by AD. On an on-premise installation was required. This has worked well for us, though it was not a simple exercise to set it up initially.
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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 (24)
    8.5
    85%
  • Connect to Multiple Data Sources (23)
    8.4
    84%
  • Extend Existing Data Sources (24)
    8.1
    81%
  • Automatic Data Format Detection (23)
    7.1
    71%

Reviewer Pros & Cons

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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

Posit Connect | Host all of the data products you create
YouTube
What is Posit Workbench? Build Data Products in R & Python using Jupyter, VSCode, and RStudio.
YouTube
J.J. Allaire | Open Source Software for Data Science | RStudio (2020)
41:00
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Features

Platform Connectivity

Ability to connect to a wide variety of data sources

7.9Avg 8.2

Data Exploration

Ability to explore data and develop insights

8.4Avg 8.0

Data Preparation

Ability to prepare data for analysis

8.2Avg 8.0

Platform Data Modeling

Building predictive data models

8.3Avg 8.2

Model Deployment

Tools for deploying models into production

7.9Avg 8.3
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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 Integrations

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

Reviewers rate Single platform for multiple model development highest, with a score of 8.6.

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

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Reviews

(1-25 of 121)
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Score 9 out of 10
Vetted Review
Verified User
We use RStudio to process large amounts of data, both for importing into other systems and after exporting back from them. Other uses cases include performing statistical analysis and creating visualisations. RStudio makes it easy to perform complex manipulations on large datasets and automate long complicated processes, saving us a ton of time and removes the potential of human error.
Score 8 out of 10
Vetted Review
Verified User
RStudio helps our large team of conservation researchers address problems relating to data management, cleaning, and processing. In addition, it also helps our team with database management as we often manage large and historical sets of data. In many cases, our teams are using RStudio for the analysis of field data to assist with international conservation programs.
Score 9 out of 10
Vetted Review
Verified User
We use RStudio as an analysis tool to perform complex data analysis problems and scenarios. We build different statistical models to understand business data and perform forecasts. It has good visualizations and is a very flexible tool. As Business Analyst it is a good tool to understand big data in the organization.
Akshat Garg | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
We use RStudio to build data science and machine learning pipelines for AI models. The pipeline that we create on R studio help in end-to-end data processing, cleaning, RDA, model training, and prediction. The scripts that we write on RStudio are also used for automation and creating machine learning tools using R shiny as well.
Score 10 out of 10
Vetted Review
Verified User
I have used the R language since around 2010 and before (along with S-Plus). RStudio as soon as it was available, also around 2010. Example use cases: 1. bionanoengineering - descriptive statistics (describing biological motility or nano surfaces), in parallel with image analysis in ImageJ and MATLAB; 2. bioinformatics - producing descriptive statistics for the motility of Neurospora crassa (filamentous fungus) to prove that how one use statistics matters and how it impacts business decisions; 3. pharma - benefit-risk analysis and data visualizations along with Spotfire 4. healthcare - clinical programming along with Stata and Python (one suggestion: it would be nice to have R interface in Stata and improved R interface in Spotfire); 5 - in product development for creating data monitoring & evaluation apps in RShiny. RStudio has been with me since the very beginning of my professional career. I could easily write up a Ph.D. on the use cases of R in life sciences, pharma, healthcare, and computer science. I would highly recommend RStudio for those who need to deliver fast tailored, customized applications, attractive visualizations or need to use Bayesian statistics, for example, to validate pharmacovigilance scores.
Score 10 out of 10
Vetted Review
Verified User
It is used by the Data Science team within the department. It helps the team with the reporting functions, tackles business problems from an analytical perspective, and builds up quick interactive tools.
Andrew Choens | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
We license the RStudio Connect (RSC) product from RStudio. We also use, for free, the open source packages and development environment offered by RStudio. Without going into specifics, our Connect license is about 1/6th the cost of our QlikView license, which we will discontinue once we are done porting legacy dashboards off of it. A direct comparison between Qlik and RSC is unfair. Products such as QlikView and PowerBI are BI tools which licensed users use to build dashboards. I refer to RSC as a content management platform for data science. We use it to: Validate our data and alert us to problems. Email reports to clients in PDF and Excel. Upload data to FTP servers and to send HL7 messages (via a HL7 engine). Hosts our internal API. Host machine learning models. Host custom-built dashboards. And, staff love developing against it.I could calculate an ROI for everything, except staff satisfaction. But the value add is there and it is valuable.
Score 8 out of 10
Vetted Review
Verified User
RStudio is used in my organization to build machine learning models, such as linear regression, logistic regression, decision trees, random forest, k-mean clustering, and more. It solves our business problem of having a low-cost, open-source tool for building statistical models and running models for data analysis. We can also use this for data visualization and data cleaning.
Score 6 out of 10
Vetted Review
Verified User
RStudio is used as a supporting program for graduate-level courses, such as Experimental Research Methods. It helps students understand how to clean, analyze, and visualize quantitative data. The scope of my use case is 10-week courses that have used RStudio in different ways, i.e., information visualization and data transformation.
Score 8 out of 10
Vetted Review
Verified User
We are using RStudio for quick querying, reading, and writing tables on the backend for the sole purpose of product analytics. RStudio is the go-to interface, and with easy installation of ODBC drivers on Windows machines, it provides great utility to connect to the Amazon Redshift database. It is an important piece in our analytics framework, as the custom tables created through this interface are used for visualizations on other software.
Score 10 out of 10
Vetted Review
Verified User
R is primarily used as a data cleaning tool (in our team) which is agnostic to user machines, thus creating a repeatable workflow. Earlier, we used both Power Query and Alteryx for it. Power Query used to take a lot of time, and Alteryx turned out to be a pretty expensive affair. For our reporting purpose, we had to collate many files, and after doing some manipulation by removing duplicates and other process-related activities, we had to create some metrics. All were done in RStudio, and then the output is used to upload in DWH.
Score 8 out of 10
Vetted Review
Verified User
Currently, we use RStudio within our group as the primary way to interact with R and particularly R scripts for automated analysis of large datasets. We've also used RStudio to develop Shiny GUIs to provide a user-friendly interface for these R scripts for others in our organization that may be less familiar with running scripts in RStudio.
Jim Gruman | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
We use RStudio for analytics, data science, reporting, and statistical modeling for business clients in all enterprise functional groups. The system is extensible to a wide array of use cases, including quality, machine reliability, finance, supply chain, marketing, and business intelligence. RStudio connects to our Azure and on-premise data assets.
Kunal Sonalkar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
We are using RStudio to develop shiny web applications and develop predictive data models. We perform statistical analysis on the data and try to gain insights from it.

With the shiny apps, we are automating routine excel reports which saves a lot of time for database and business analysts.

We have written numerous algorithms in RStudio like Naive Bayesian Classification, K-Means Clustering and ARIMA modelling.

RStudio is an amazing platform for statistical data analysis.
Suryaprakash Mishra | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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.
Chris Beeley | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
My team uses RStudio products, but we distribute reports and dashboards to 100+ users. The business problem it addresses is how to get the data science work that we're doing in R and Python (for example, text mining), as well as more day-to-day reporting based on some of the data structures that we have written in R/SQL.
Kenton Woods | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
RStudio is currently used to analyze data. It makes using R much easier for us researchers and allows us to test our hypotheses. It is used by researchers across the department to do quantitative analyses using data we have collected. We use it for social network analyses that include friendship nominations.
Bobbi Woods | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
We use RStudio for statistics-related endeavors on our research projects. We use it frequently for accessing and analyzing our data in descriptive and predictive type analyses. It helps us address issues such as underperformance in schools and other education settings, or even issues of inequity and exclusion of vulnerable populations.
January 20, 2022

Hooray RStudio.

Score 8 out of 10
Vetted Review
Verified User
Our internal analytical platform is deeply connected with a series of RStudio products, from RStudio Connect to RSPM. These products provide not only great development environment, but they also create the excellent user experience for customers. Importantly, the RStudio support team is very responsive. The team takes customer's request very seriously, and if there is no immediate solution, they usually follow up with a long-term plan. Shout out to our main contact Colin.
Score 9 out of 10
Vetted Review
Verified User
I use RStudio to produce descriptive and predictive analytics surrounding various business products. My analytics help higher-ups understand the efficiencies and problem areas in business processes and make evidence-based decisions. The data visualizations I generate in [RStudio] are especially instrumental in presenting accurate, easily consumable metrics for lay audiences.
January 18, 2022

RStudio is wonderful!

Score 9 out of 10
Vetted Review
Verified User
I am the primary statistician on my team and I use RStudio almost exclusively to perform the product efficacy analyses. I use RStudio to automate many of our data cleanup processes and also run dynamic analyses to answer our research questions.
Prashast Vaish | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
I am working with an Australian supermarket giant and helping them analyze data for their e-commerce business. RStudio helps me in getting the raw data from various sources and cleaning them up so that they can be aggregated and visualized in a BI tool for insight generation to improve the business performance.
Jacob Benzaquen | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
I currently use RStudio to create and develop 3D maps for ground-mounted solar arrays to better account for the terrain where they will be placed. It is also used for statistical analysis within the company to determine where the best placement for the solar arrays will be within the topography.
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