Revolution Analytics

Revolution Analytics was a statistical-software company founded in 2007 in New Haven, Connecticut, initially under the name REvolution Computing. Its business was built around R, the free and open-source programming language and environment widely used for statistics, data analysis, and academic research. The company pursued an open-core model: improvements to core R and related open-source components were distributed under open-source licenses, while commercial customers paid for enterprise software, technical support, assurance, deployment options, and proprietary extensions. The company was established by Richard Schultz, Martin Schultz, Steve Weston, and Kirk Mettler. Martin Schultz was also associated with Yale University as a computer-science professor. REvolution Computing initially concentrated on making R more useful for commercial and technically demanding workloads, especially by adding parallel-processing capabilities to an ecosystem that was historically constrained by single-threaded execution and in-memory data handling. Its early customers included pharmaceutical and life-sciences organizations, where the ability to run statistical workloads across computing clusters could materially improve processing speed. A significant change came in 2009, when the company accepted approximately $9 million in venture financing from Intel and North Bridge Venture Partners. Intel had previously supported the business, and several Intel personnel subsequently became employees or advisers. Around the same period, REvolution Computing adopted the name Revolution Analytics and appointed Norman H. Nie, a founder of SPSS, as chief executive. The rebranding reflected a broader strategy: rather than primarily selling support and parallel-computing additions, the company aimed to provide a fuller commercial analytics platform for large datasets, multiprocessor systems, and enterprise users. David Rich succeeded Nie as chief executive in February 2012. In 2010, Revolution Analytics introduced ScaleR as part of Revolution R Enterprise. ScaleR addressed the practical limitations of conventional R workflows by supporting disk-based processing through the XDF data store and distributed or high-performance computation across clusters. It was designed to work with Hadoop and other distributed file systems, and the company pursued integrations with IBM and the broader Hadoop ecosystem. This product direction moved the business toward packaged software and subscription offerings rather than consulting and services alone. The company’s product portfolio eventually included Revolution R Open, a free distribution of R with performance and reproducibility enhancements; Revolution R Plus, which combined open-source components with technical support and open-source assurance; and Revolution R Enterprise, which added proprietary big-data and high-performance capabilities for workstations, servers, Hadoop environments, and databases. Academic users and participants in certain data-science competitions could access selected enterprise capabilities without charge, while commercial customers generally purchased subscriptions or support. Revolution Analytics positioned itself against established proprietary analytics vendors such as SAS by emphasizing R’s openness, programmability, and large academic and developer community. Its commercial opportunity depended on organizations adopting open-source analytical methods while still requiring enterprise support, governance, scalability, and integration with existing infrastructure. The company remained relatively small compared with major analytics-software suppliers, but it benefited from the growing use of R in academia, life sciences, finance, and data science. Microsoft announced an agreement to acquire Revolution Analytics on January 23, 2015, for an undisclosed amount. After the acquisition, Microsoft rebranded or incorporated several products, including Microsoft R Server, Microsoft R Open, Microsoft R Server Developer Edition, and the Microsoft Data Science Virtual Machine. The independent Revolution Analytics brand therefore ceased to operate as a standalone company. Microsoft later announced the retirement of its R distribution in 2021 and retired the Microsoft R Application Network in 2023, ending important parts of the product and package-distribution infrastructure inherited from Revolution Analytics.

Revolution Analytics began in 2007 as REvolution Computing in New Haven, Connecticut. Its founders were Richard Schultz, Martin Schultz, Steve Weston, and Kirk Mettler. The company was formed to provide commercial support and services around R, an open-source statistical-computing environment, while also developing extensions that could make R more effective on parallel and clustered systems. The founders’ approach resembled the commercial model used by companies supporting open-source infrastructure: customers could use the underlying open software, while the vendor sold support, services, assurance, and additional enterprise functionality. The early technical focus reflected a limitation of conventional R at the time. Many R workloads were constrained by single-threaded execution and the requirement that working data fit into memory. REvolution Computing developed parallel-processing improvements and related tools to make R more practical for large institutional users. Pharmaceutical and life-sciences organizations were among the early adopters, with companies such as Pfizer using the technology to accelerate analytical jobs on computing clusters. The company also opened an additional office in Seattle approximately a year after its founding. In 2008, Intel provided early venture support. In 2009, REvolution Computing received approximately $9 million from Intel and North Bridge Venture Partners. The financing coincided with a shift in corporate identity and strategy. The business became Revolution Analytics, and Norman H. Nie, associated with the founding of SPSS, became chief executive. The new direction sought to broaden the company from a provider of parallel R support into a more complete enterprise analytics vendor. The company emphasized big-data processing, high-performance computing, multicore execution, and commercial software for organizations that needed more than the standard community distribution of R. The company’s main technical milestone in this period was ScaleR, introduced in 2010 as part of Revolution R Enterprise. ScaleR supplied algorithms and data-handling capabilities intended for datasets too large or complex for ordinary in-memory processing. Its XDF disk-based storage model supported larger workflows, while cluster-oriented functions enabled distributed computation. ScaleR could work with Hadoop and other distributed file systems, and Revolution Analytics pursued cooperation with IBM to connect R-based analytics with Hadoop deployments. This was strategically important because the company was competing in a market increasingly defined by large datasets and distributed infrastructure rather than desktop statistics alone. Revolution Analytics developed a tiered product model. Revolution R Open provided a free distribution with performance and reproducibility features. Revolution R Plus added technical assistance and open-source assurance, including support for selected open-source components. Revolution R Enterprise combined the R environment with proprietary capabilities for big-data analytics and high-performance execution, with deployment options for workstations, servers, Hadoop, and databases. Academic users and some data-mining competitors could receive selected products at no cost, while commercial users were served through subscriptions and support arrangements. The company’s competitive identity rested on the contrast between R’s open, programmable ecosystem and the more closed or specialized products of established analytics vendors such as SAS. Revolution Analytics argued that R’s popularity in universities and among researchers created a large base of technically sophisticated users who would eventually need supported enterprise implementations. The company also benefited from broader interest in open-source software and a movement away from opaque, black-box analytical systems toward tools that allowed users to inspect, extend, and share code. Norman Nie left the chief executive role in 2012, when David Rich became CEO. The company continued to develop enterprise R offerings and expand integrations with databases, Hadoop, and operating-system platforms. On January 23, 2015, Microsoft announced that it had agreed to acquire Revolution Analytics. The financial terms were not disclosed in the referenced sources. Following the transaction, Microsoft folded the company’s technology and products into its data-platform strategy and renamed several offerings. Revolution R Enterprise for Hadoop, Linux, and Teradata became associated with Microsoft R Server; Revolution R Open became Microsoft R Open; and Microsoft introduced related developer and virtual-machine offerings. The acquisition ended Revolution Analytics as an independent corporate brand, but its technology continued under Microsoft branding for several years. Microsoft later announced the retirement of its R distribution in 2021 and discontinued the Microsoft R Application Network in 2023. These later changes marked the winding down of significant services and product infrastructure inherited from the company.

• 2023

  Microsoft R Application Network is retired

  [1]Revolution Analyticsen.wikipedia.org

  Microsoft discontinued the proprietary package-hosting network associated with inherited Revolution Analytics products.

• 2021

  Microsoft announces retirement of its R distribution

  [1]Revolution Analyticsen.wikipedia.org

  Microsoft announced that it would retire the R distribution obtained through the Revolution Analytics acquisition.

• 2015

  Microsoft agrees to acquire the company

  [2]Microsoft to acquire Revolution Analyticsnews.microsoft.com

  Microsoft announced an agreement to acquire Revolution Analytics for an undisclosed amount.

• 2014

  Revolution R Open and Revolution R Plus announced

  [1]Revolution Analyticsen.wikipedia.org

  The company announced free open-source and supported-assurance editions designed to broaden adoption of its R-based platform.

• 2012

  David Rich becomes CEO

  [1]Revolution Analyticsen.wikipedia.org

  David Rich succeeded Norman H. Nie as chief executive.

• 2010

  ScaleR is introduced

  [1]Revolution Analyticsen.wikipedia.org

  ScaleR added disk-based and distributed-processing capabilities to Revolution R Enterprise for larger datasets and high-performance computing.

• 2009

  Company renamed Revolution Analytics

  [1]Revolution Analyticsen.wikipedia.org

  The business changed its name from REvolution Computing to Revolution Analytics and appointed Norman H. Nie as chief executive.

• 2009

  Approximately $9 million financing round

  [1]Revolution Analyticsen.wikipedia.org

  Intel and North Bridge Venture Partners provided approximately $9 million in venture financing.

• 2008

  Intel provides early venture support

  [1]Revolution Analyticsen.wikipedia.org

  Intel supported the young company with venture financing before participating in a larger financing round the following year.

• 2007

  REvolution Computing is founded

  [1]Revolution Analyticsen.wikipedia.org

  Richard Schultz, Martin Schultz, Steve Weston, and Kirk Mettler founded the company in New Haven, Connecticut, to commercialize support, services, and performance extensions for the R statistical-computing environment.

Enterprise-grade analytics built around the open-source R language, combining community software with commercial support, performance optimization, distributed computing, and big-data capabilities.

• Statistical-computing platform

  Revolution R

  The company’s broader R-based product family, combining the open-source R environment with performance improvements, enterprise support, and optional proprietary capabilities. It served academic, developer, and commercial users and was offered in multiple editions as Revolution Analytics refined its open-core business model.

• Open-source R distribution · 2014

  Revolution R Open

  A free distribution of R enhanced for performance and reproducibility. It was intended to provide a readily deployable version of R while preserving the open-source character of the underlying environment. Microsoft later rebranded the offering as Microsoft R Open.

• Support and assurance subscription · 2014

  Revolution R Plus

  A commercial support tier for Revolution R Open and related open-source components. It added technical assistance and open-source assurance, including legal indemnification features, allowing organizations to adopt R with a vendor-backed support relationship.

• Enterprise analytics platform

  Revolution R Enterprise

  The company’s principal commercial platform for large-scale statistical analysis. It combined R with proprietary extensions for big-data processing, high-performance computing, and distributed deployment across workstations, servers, Hadoop environments, and databases. Selected academic and competition users could access versions without charge, while commercial customers purchased subscriptions.

• Big-data analytics extension · 2010

  ScaleR

  A package within Revolution R Enterprise designed for data volumes and workloads beyond standard in-memory R processing. It used the XDF disk-based data store and supported high-performance computation across clusters, Hadoop, and other distributed file systems.

• Successor enterprise analytics product · 2015

  Microsoft R Server

  A Microsoft-branded successor to Revolution R Enterprise for environments including Hadoop, Linux, and Teradata. It extended the commercial R technology acquired from Revolution Analytics with Microsoft support, distribution, and purchasing options.

• 2015

  Sale to MicrosoftM&A

  Background

  Microsoft was expanding its data-platform and data-science capabilities, while Revolution Analytics had developed commercial technology around the widely used R ecosystem.

  Action taken

  Microsoft agreed to acquire Revolution Analytics. The purchase price was not disclosed in the referenced material.

  Aftermath

  The independent company and brand were absorbed into Microsoft, with products rebranded as Microsoft R Server, Microsoft R Open, and related offerings.

  Source

• 2010

  Launch of ScaleRProduct launch

  Background

  Standard R workflows often required data to fit in memory and were not optimized for distributed cluster processing.

  Action taken

  Revolution Analytics introduced ScaleR, using disk-based XDF storage and distributed high-performance processing for large datasets.

  Aftermath

  The company moved further from services-led work toward packaged enterprise software and integrations with Hadoop and other distributed systems.

  Source

• 2009

  Shift from R support toward enterprise analyticsStrategy

  Background

  The company had initially emphasized support services and parallel-processing improvements for R. Growing demand for large-scale analytics created an opportunity to sell a broader commercial platform.

  Action taken

  It adopted the Revolution Analytics name, appointed Norman H. Nie as CEO, and focused its commercial roadmap on big data, multiprocessor computing, and multicore performance.

  Aftermath

  The change led to a product portfolio centered on Revolution R Enterprise and related subscription, support, and high-performance offerings.

  Source

1. 1Revolution Analyticsen.wikipedia.org
2. 2Microsoft to acquire Revolution Analyticsnews.microsoft.com