A data science platform
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RStudioProduct Overview

  1. About RStudio
  2. Pros of RStudio
  3. Cons of RStudio
  4. Breakdown of core features

RStudio product overview

RStudio is a data science platform that includes open source and enterprise-ready commercial products. It is a modular platform that includes data science software and other professional software products that enable teams to adopt R, Python, and other open-source data science software at scale. The software provides an integrated development environment (IDE) for R and Python with a modern console, editor, and tools.
RStudio creates free and open-source software for communities and organizations that work on data science, scientific research, technical communication, and any other data analysis. It also creates commercial products whose revenue enables ongoing sustainable investment in open source software that benefits all users. The company spends 50 percent of its engineering resources on open source software development and provides support to the open source data science community.

Pros of RStudio

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  • Code-friendly: RStudio uses modern tools such as a syntax-highlighting editor that supports direct code execution. Its core productivity tools, packages, protocols, and file formats are open source and do not force customers to be dependent on a single vendor.
  • Modular, scalable, and production-ready: RStudio is modular and allows companies to use only the products they need without massive investment up front. The modular platform can scale to a large number of users and huge amounts of data. The enterprise-ready solution can also integrate into existing systems, platforms, standards, and processes.

Cons of RStudio

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  • Data science tool: RStudio is a platform specific for data scientists who are knowledgeable with the R and/or Python language. Business users will depend on the work of data scientists to discover relevant information.
  • Documentation: Some users would like to see clearer documentation of its features and offerings.

Breakdown of core features

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Data analysis

RStudio provides data scientists the software to analyze data and create data products using R and Python. RStudio Server Pro is the preferred IDE of professional R users and data science teams. It enables professional teams to operate at scale with collaboration, centralized management, metrics, security, and commercial support features. Some of these features include remote interactive sessions, remote job submission, Jupyter Notebooks, using multiple versions of R, and running multiple concurrent R and Python sessions.

Results publishing

RStudio Connect is a publishing platform that allows users across the organization to collaborate using the work created by data science teams. Discoveries by the team can be easily shared with business users to develop best practices, read reports, gain insights and make decisions, integrate data products, and scale and support IT tools without having to learn R or Python. Features include interactive applications and APIs, a platform to share data and schedule model updates, creation of emails from code, and git integration.

Package management

IT administrators use RStudio Package Manager to control and manage R packages that data scientists have created to share data products. It lets users control and distribute packages throughout the organization. The software includes a repository management server to organize and centralize packages. Users can share local packages, restrict package access, and find packages across repositories with a reliable and consistent experience.

(Last updated on 02/02/2022 by Abby Dykes)

Quick Facts

  • Industry Specialties
    All Industries
  • Pricing
  • Works Best For
    Any Sized Businesses




  • Data analysis
  • Results publishing
  • Package management
  • R/Python development
  • Load balancing
  • Tutorial API
  • Data connectivity
  • Collaboration and project sharing
  • Scale with Kubernetes and SLURM
  • Authentication, access, & security
  • Multiple concurrent sessions
  • Remote execution


  • Microsoft SQL Server
  • Oracle
  • PostgreSQL
  • Amazon Redshift
  • Amazon Athena
  • Google BigQuery
  • Salesforce
  • Apache Cassandra
  • Apache Hive
  • Apache Impala
  • Teradata
  • MySQL

Pricing Model

  • Open source
  • Standard
  • Enterprise


  • Supports multiple languages