We performed a comparison between IBM SPSS Modeler, IBM SPSS Statistics, and RapidMiner based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"It works fine. I have not had any stability issues; it is always up."
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"Compared to other tools, the product works much easier to analyze data without coding."
"We use analytics with the visual modeling capability to leverage productivity improvements."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."
"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"It offers very good visualization."
"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"The most valuable feature is its robust statistical analysis capabilities."
"It is a modeling tool with helpful automation."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"The most valuable features are the Binary classification and Auto Model."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"The challenge for the very technical data scientists: It is constraining for them."
"It is not integrated with Qlik, Tableau, and Power BI."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"Customer support is hard to contact."
"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."
"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."
"Requires more development."
"The product does not have a search function for tags."
"The statistics should be more self-explanatory with detailed automated reports."
"The solution needs to improve forecasting using time series analysis."
"It could provide even more in the way of automation as there are many opportunities."
"There is a learning curve; it's not very steep, but there is one."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"The solution needs more planning tools and capabilities."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"In the Mexican or Latin American market, it's kind of pricey."
"The price of this solution should be improved."
"It would be helpful to have some tutorials on communicating with Python."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
