Dataiku vs RapidMiner comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.2
Number of Reviews
7
Ranking in other categories
No ranking in other categories
RapidMiner
Ranking in Data Science Platforms
6th
Average Rating
8.6
Number of Reviews
22
Ranking in other categories
Predictive Analytics (3rd)
 

Mindshare comparison

As of June 2024, in the Data Science Platforms category, the mindshare of Dataiku is 9.9%, up from 6.7% compared to the previous year. The mindshare of RapidMiner is 8.3%, up from 6.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
Unique Categories:
No other categories found
Predictive Analytics
20.0%
 

Featured Reviews

GN
Nov 28, 2019
Good data preparation tools and integrates well with BigQuery
From an administrative point of view, I would like to be able to communicate with the users who are logged into the system. For example, I would like to be able to send a broadcast message that says "I am shutting down the system." I would like to see more organization and better cohesion within the tool. 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. I would like to have a better way to manage images and sound. The error messages are not self explanatory and can sometimes be difficult to understand.
AA
Aug 30, 2023
Easy to use and has a huge community
RapidMiner interacts well with data. It is valuable, easy to use, and easy to look at, and that is awesome.  It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive.  In terms of the UI and SaaS, the user interface with KNIME is more appealing than…

Quotes from Members

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

Pros

"The most valuable feature is the set of visual data preparation tools."
"The solution is quite stable."
"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."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"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."
"Data Science Studio's data science model is very useful."
"One of the most valuable features is the built-in data tuning feature. Once the model is built, we often struggle to increase its accuracy, but RapidMiner allows us to fine-tune variables. For Example, when working on a project, we can adjust the number of nodes or the depth of trees to see how accuracy changes. This flexibility lets us achieve higher accuracy compared to traditional automated machine-learning models"
"Using the GUI, I can have models and algorithms drag and drop nodes."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"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."
"The most valuable features are the Binary classification and Auto Model."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
 

Cons

"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."
"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."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"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."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"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."
"In the Mexican or Latin American market, it's kind of pricey."
"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"The product must provide data-cleaning features."
"If they could include video tutorials, people would find that quite helpful."
"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."
"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."
 

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."
"Pricing is pretty steep. Dataiku is also not that cheap."
"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."
"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."
"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
"For the university, the cost of the solution is free for the students and teachers."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Manufacturing Company
8%
Computer Software Company
7%
University
11%
Computer Software Company
11%
Educational Organization
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
Pricing is pretty steep. Dataiku is also not that cheap. It depends on the client and how much they want to spend towards a tool.
What needs improvement with Dataiku Data Science Studio?
The no-code/low-code aspect, where DataRobot doesn't need much coding at all. Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot m...
What is your primary use case for Dataiku Data Science Studio?
My current client has Dataiku. We do sentiment analysis and some small large language models right now. We use Dataiku as a Jupyter Notebook. We use it a lot for marketing and analytics. The market...
What do you like most about RapidMiner?
RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the dat...
What needs improvement with RapidMiner?
One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome t...
 

Comparisons

 

Also Known As

Dataiku DSS
No data available
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Find out what your peers are saying about Dataiku vs. RapidMiner and other solutions. Updated: May 2024.
787,779 professionals have used our research since 2012.