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- Visualization (23)8.888%
- Connect to Multiple Data Sources (22)8.484%
- Extend Existing Data Sources (23)8.383%
- Automatic Data Format Detection (22)7.575%
Entry-level set up fee?
- Setup fee optional
- Free Trial
- Free/Freemium Version
- Premium Consulting / Integration Services
Would you like us to let the vendor know that you want pricing?
RStudio is a modular data science platform, combining open source and commercial products.
The vendor states their open source offerings, such as the RStudio IDE, Shiny, rmarkdown and the many packages in the tidyverse, are used by millions of data scientists around the world to enhance the production and consumption of knowledge by everyone, regardless of economic means.
Their commercial software products, including RStudio Workbench, RStudio Connect, and RStudio Package Manager, are available as a bundle in RStudio Team. These products aim to give organizations the confidence to adopt R, Python and other open-source data science software at scale. This enables data science teams using R and Python to deliver interactive reports and applications to decision makers, leverage large amounts of data, integrate with existing enterprise systems, platforms, and processes, and be compliant with security practices and standards.
The platform is complemented by online services, including RStudio Cloud and shinyapps.io, to make it easier to do, teach and learn data science, and share data science insights with others, over the web.
Together, RStudio’s open-source software and commercial software form a virtuous cycle: The adoption of open-source data science software at scale in organizations creates demand for RStudio’s commercial software; and the revenue from commercial software, in turn, enables deeper investment in the open-source software that benefits everyone.
- Supported: Connect to Multiple Data Sources
- Supported: Extend Existing Data Sources
- Supported: Automatic Data Format Detection
- Supported: Visualization
- Supported: Interactive Data Analysis
- Supported: Interactive Data Cleaning and Enrichment
- Supported: Data Transformations
- Supported: Multiple Model Development Languages and Tools
- Supported: Single platform for multiple model development
- Supported: Self-Service Model Delivery
- Supported: Flexible Model Publishing Options
- Supported: Security, Governance, and Cost Controls
- Supported: Share Data Science insights in the form of Shiny applications, R Markdown reports, Plumber APIs, dashboards, Jupyter Notebooks, interactive Python content, and more.
- Jupyter Notebook
- Apache Spark
- Databricks Lakehouse Platform (Unified Analytics Platform)
- Dash applications
- VS Code
- SAML Marketplaces
|Deployment Types||On-premise, SaaS|
|Operating Systems||Windows, Linux, Mac|
However I am not happy with the current pricing model. Not enough hours are allotted in the free tier for students to handle the workload of an applied stats class. In the shared workspace model where students "charge" their hours toward the instructor's workspace, that is far too few hours to handle a typical class size of 30, let alone larger class sizes. The expectation that a faculty member (or department) will pay out of pocket upwards of $800 for a typical class of 30 is unrealistic.