RapidMiner Review

Features Include Cutting-Edge Data Science Tools and Algorithms

What is our primary use case?

RapidMiner is primarily used to develop and deploy machine learning workflows to real business use cases, e.g. predictive analytics, segmentation, etc...

How has it helped my organization?

As a data science consultant, I was able to custom-build a machine learning lead generation (web scraping) tool for a client and have it be operational in 72 hours.

What is most valuable?

  1. Availability of cutting-edge data science tools and algorithms
  2. Ease of code-optional GUI
  3. Open Source Java core
  4. Easy integration with APIs, Python, R, cloud storage, cloud computing, etc.

What needs improvement?

I would like to see wider adoption of the RapidMiner platform by the Open Source community as a viable alternative/companion to Python and R.

For how long have I used the solution?

More than five years.

What do I think about the stability of the solution?


What do I think about the scalability of the solution?


How are customer service and technical support?


Which solution did I use previously and why did I switch?

I used to use Excel. It was horrid.

How was the initial setup?

Not at all. Lots of YouTube videos and documentation. Super easy.

What's my experience with pricing, setup cost, and licensing?

RapidMiner has a freemium pricing model so, as long as your dataset has fewer than 10,000 rows, you have free software. There is also free academic licensing for Higher Ed or researchers. For companies, RapidMiner's paid license is much cheaper than SAS, SPSS, or other competitors. You definitely get your money's worth.

Which other solutions did I evaluate?


What other advice do I have?

Sign up and read what others do with RapidMiner on the user community (community.rapidminer.com).

Which version of this solution are you currently using?

Studio 8.0.1
**Disclosure: I am a real user, and this review is based on my own experience and opinions.
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