| Category | Description | Open Source Edition | Professional Edition |
|---|---|---|---|
| Overview | Access the RStudio IDE from anywhere via a web browser | ||
| Move computation close to the data | |||
| Scale compute and RAM centrally | |||
| Powerful coding tools to enhance your productivity | |||
| Easily publish apps and reports | |||
| Python Development | View Python data, publish and knit in Python and share objects with R | ||
| Author and edit Python code with Jupyter Notebooks, JupyterLab and VSCode | |||
| Easily publish and share Jupyter Notebooks | |||
| Project Sharing | Share projects & edit code files simultaneously with others | ||
| Multiple R Versions | Run multiple versions of R side-by-side | ||
| Define environments for a particular R version | |||
| Multiple R and Python Sessions | Run multiple analyses in parallel | ||
| Load Balancing | Load balance R sessions across two or more servers | ||
| Ensure high availability using multiple masters | |||
| Administrative Dashboard | Monitor active sessions and their CPU and memory utilization | ||
| Suspend, forcibly terminate, or assume control of any active session | |||
| Review historical usage and server logs | |||
| Enhanced Security | LDAP, Active Directory, Google Accounts and system accounts | ||
| Full support for Pluggable Authentication Modules, Kerberos via PAM, and custom authentication via proxied HTTP header | |||
| Encrypt traffic using SSL and restrict client IP addresses | |||
| Auditing and Monitoring | Monitor server resources (CPU, memory, etc.) on both a per-user and system-wide basis | ||
| Send metrics to external systems with the Graphite/Carbon plaintext protocol | |||
| Health check with configurable output (custom XML, JSON) | |||
| Audit all R console activity by writing input and output to a central location | |||
| Advanced R Session Management | Tailor the version of R, reserve CPU, prioritize scheduling and limit resources by User and Group | ||
| Provision accounts and mount home directories dynamically via the PAM Session API | |||
| Automatically execute per-user profile scripts for database and cluster connectivity | |||
| Data Connectivity | RStudio Professional Drivers are ODBC data connectors that help you connect to some of the most popular databases | ||
| Launcher | Start processes within various systems such as container orchestration platforms | ||
| Submit standalone ad hoc jobs to your compute cluster(s) to run computationally expensive R or Python scripts | |||
| Tutorial API | Automate interactions with the RStudio IDE | ||
| Remote Sessions | Connect to RStudio Workbench directly from RStudio Desktop Pro for more powerful computing resources, freeing up your local system |
Differences Between R Studio For Windows And Mac
I’ve installed R on Windows 7 and Windows 8 machines without any issues. By default the installation process gives you both 32-bit and 64-bit versions. This article assumes you have at least intermediate C# programming skills (so you can understand the explanations of the similarities and differences between C# and R), but doesn’t assume.
My Heterodox Take Of The Problem: I Concur With Feyerabend That Knowing The History Of The Concepts Is The Best Way To Teach And Understand It. Pos...
RStudio Desktop is an R IDE that works with the version of R you have installed on your local Windows, Mac OS X, or Linux workstation. RStudio Desktop is a standalone desktop application that in no way requires RStudio Workbench or RStudio Server. R is a cross-platform programming which can run on any operating system. R has a rich set of packages. Below is a table of differences between MATLAB and R Programming Language: Based on. R Programming Language. Matlab is a high-performance language. R is an interpreted language.