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Dataiku vs SAS Enterprise Miner comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

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

Categories and Ranking

Dataiku
Ranking in Data Science Platforms
6th
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
No ranking in other categories
SAS Enterprise Miner
Ranking in Data Science Platforms
18th
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
13
Ranking in other categories
Data Mining (7th)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.7%, up from 8.2% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.7%, down from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

RichardXu - PeerSpot reviewer
The platform organizes workflows visually and efficiently
One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.
reviewer1352853 - PeerSpot reviewer
A stable product that is easy to deploy and can be used for structured and unstructured data mining
We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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 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."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"Data Science Studio's data science model is very useful."
"The solution is quite stable."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"Good data management and analytics."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"I like the way the product visually shows the data pipeline."
"The solution is able to handle quite large amounts of data beautifully."
 

Cons

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"We still encounter some integration issues."
"There is room for improvement in terms of allowing for more code-based features."
"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."
"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 solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The initial setup is challenging if doing it for the first time."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The user interface of the solution needs improvement. It needs to be more visual."
"The solution is much more complex than other options."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"Technical support could be improved."
"The product must provide better integration with cloud-native technologies."
 

Pricing and Cost Advice

"Pricing is pretty steep. Dataiku is also not that cheap."
"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."
"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
"This solution is for large corporations because not everybody can afford it."
"The solution must improve its licensing models."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Educational Organization
13%
Manufacturing Company
9%
Computer Software Company
9%
Financial Services Firm
25%
University
12%
Educational Organization
9%
Manufacturing Company
8%
 

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?
The pricing for Dataiku is very high, which is its biggest downside. The model they follow is not consumption-based, making it expensive.
What needs improvement with Dataiku Data Science Studio?
Dataiku's pricing is very high, and commercial transparency is a challenge. Support is also an area needing improvement. More features like LLM security, holographic encryption, and enhanced GPU in...
What is your primary use case for Dataiku Data Science Studio?
My primary use case for Dataiku ( /products/dataiku-reviews ) is for data science, Gen ( /products/gen-reviews ) AI, and data science applications. Our AGN team also uses it for various purposes.
What do you like most about SAS Enterprise Miner?
I like the way the product visually shows the data pipeline.
What is your experience regarding pricing and costs for SAS Enterprise Miner?
The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pric...
What needs improvement with SAS Enterprise Miner?
The product must provide better integration with cloud-native technologies.
 

Comparisons

 

Also Known As

Dataiku DSS
Enterprise Miner
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Find out what your peers are saying about Dataiku vs. SAS Enterprise Miner and other solutions. Updated: March 2025.
845,712 professionals have used our research since 2012.