Compare Dataiku Data Science Studio vs. RapidMiner

Dataiku Data Science Studio is ranked 12th in Data Science Platforms with 4 reviews while RapidMiner is ranked 4th in Data Science Platforms with 8 reviews. Dataiku Data Science Studio is rated 7.6, while RapidMiner is rated 8.2. The top reviewer of Dataiku Data Science Studio writes "User interface is colorful, beautiful, and well-designed but sometimes the solution can be slow". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". Dataiku Data Science Studio is most compared with Alteryx, KNIME and Databricks, whereas RapidMiner is most compared with KNIME, Alteryx and H2O.ai. See our Dataiku Data Science Studio vs. RapidMiner report.
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Most Helpful Review
Find out what your peers are saying about Dataiku Data Science Studio vs. RapidMiner and other solutions. Updated: January 2020.
389,978 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person.The most valuable feature is the set of visual data preparation tools.The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction.Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors.Cloud-based process run helps in not keeping the systems on while processes are running.

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Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations.The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS.The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model.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.RapidMiner is very easy to use.The documentation for this solution is very good, where each operator is explained with how to use it.I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries.

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Cons
I find that it is a little slow during use. It takes more time than I would expect for operations to complete.In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin.The ability to have charts right from the explorer would be an improvement.Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable.Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days).There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders.

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The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive.It would be helpful to have some tutorials on communicating with Python.The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator.A great product but confusing in some way with regard to the user interface and integration with other tools.RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.I would like to see all users have access to all of the deep learning models, and that they can be used easily.The price of this solution should be improved.The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade.

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Pricing and Cost Advice
The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything.

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The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license.Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year.I used an educational license for this solution, which is available free of charge.

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Ranking
12th
Views
7,866
Comparisons
5,723
Reviews
4
Average Words per Review
493
Avg. Rating
7.5
4th
Views
9,187
Comparisons
7,691
Reviews
8
Average Words per Review
341
Avg. Rating
8.6
Top Comparisons
Compared 14% of the time.
Compared 35% of the time.
Compared 21% of the time.
Compared 6% of the time.
Also Known As
Dataiku DSS
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Dataiku
RapidMiner
Overview

Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently.

RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.

Offer
Learn more about Dataiku Data Science Studio
Learn more about RapidMiner
Sample Customers
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAutoPayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Top Industries
VISITORS READING REVIEWS
Software R&D Company30%
Financial Services Firm16%
Comms Service Provider7%
Manufacturing Company5%
VISITORS READING REVIEWS
Software R&D Company21%
University14%
Manufacturing Company10%
Comms Service Provider9%
Find out what your peers are saying about Dataiku Data Science Studio vs. RapidMiner and other solutions. Updated: January 2020.
389,978 professionals have used our research since 2012.
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