RStudio Server Open Source vs. Pro Comparison

The premier R IDE for data professionals

RStudio Server Pro Comparison to RStudio Server Open Source

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
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 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