RapidMiner announced the release of RapidMiner 8, a significant upgrade to the architecture of the RapidMiner data science platform.
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.
Improvements include:
- 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, CPO 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.”
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