BOSTON, Dec. 5, 2017 /PRNewswire/ --RapidMiner™, the company that delivers real data science, fast and simple, today announced the release of RapidMiner 8, a significant upgrade to the architecture of the RapidMiner data science platform. In addition to the launch of RapidMiner 8, the company announced record revenue for its Q3 2017.
RapidMiner 8.0 improves the reliability and scalability of the RapidMiner platform, enabling the production, deployment, and management of enterprise-scale data science projects. At the core of RapidMiner 8 is a new architecture based on containers and microservices.
Horizontal scalability. The new distributed architecture in RapidMiner Server enables deployment across any number of machines for execution of data and machine learning processes. The allows enterprises to fluidly scale as their data science teams grow and more models are put into production.
Improved stability. RapidMiner Server now supports containerized job executions. Processes are sandboxed, and won't affect the execution of other processes to create a highly stable environment.
New user interface. RapidMiner Server introduces a new user interface designed to improve user productivity for common tasks.
New and improved machine learning algorithms. RapidMiner Studio enhancements include regression trees, extremely randomized trees, a new fuzzy operator search, and improved operator documentation.
"RapidMiner 8 is a massive milestone in the evolution of RapidMiner as an enterprise-scale data science platform," said Lars Bauerle, chief product officer at RapidMiner. "RapidMiner powers mission-critical predictive models for global enterprises, and we want to ensure that our largest customers can deploy RapidMiner in a highly scalable, reliable, and secure environment. RapidMiner 8 is just the beginning of an aggressive roadmap we have planned for our users."
RapidMiner achieved another quarter of record revenue in its Q3 2017, driven by strong new customer acquisition and one of the largest transactions in company history. Organizations continue to purchase RapidMiner for a variety of data science and machine learning initiatives, select new customers in Q3 2017 include:
An automobile manufacturer, who selected RapidMiner to improve the productivity of hundreds of data scientists across a variety of use cases including customer segmentation, product research and development, predictive maintenance, and churn prevention.
An energy company, who selected RapidMiner to allow its data science team to speed up predictive model creation and deployment, while integrating with its existing R and Python workflows.
A Fortune 500 consumer-packaged goods company, who selected RapidMiner for a demand forecasting application to improve operational performance.
"RapidMiner continues to achieve outstanding business results," said Peter Lee, chief executive officer at RapidMiner. "Our business continues to experience rapid growth, driven by a combination of innovative customers, the best data science platform for the enterprise, and the excellent team we've built. We're thrilled to release RapidMiner 8, and are looking forward to continued momentum as we head into 2018 and beyond."
RapidMiner builds a software platform for data science teams that unites data prep, machine learning, and predictive model deployment. Organizations can build machine learning models and put them into production faster than ever before on a single platform. RapidMiner eliminates the complexities of cutting edge data science by making it easy to deploy the latest machine learning algorithms and innovative technologies like Tensorflow, Hadoop, and Spark. More than 300,000 data scientists in over 150 countries use RapidMiner products on-premise or in the cloud to drive revenue, reduce costs, and avoid risks.