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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
7th
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 March 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.5%, up from 8.0% 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.
reviewer1447110 - PeerSpot reviewer
Good technical support but too complex and not open-source
We're using Enterprise Guide simultaneously with Enterprise Miner. From my perspective, I believe that open-source analytics tools are closer to fitting our needs. We prefer open-source options like Anaconda. They offer good support and features. Anaconda also integrates well with Jupyter NET, which is important for us. Overall, on a scale from one to ten, I'd rate the solution at a five. If there were better protocols and wasn't as complex as it is, I'd rate it a bit higher.

Quotes from Members

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

Pros

"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."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"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 believe the return on investment looks positive."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"I rate the overall product as eight out of ten."
"The solution is quite stable."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"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."
"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."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"The solution is very good for data mining or any mining issues."
"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."
"I like the way the product visually shows the data pipeline."
 

Cons

"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."
"There is room for improvement in terms of allowing for more code-based features."
"We still encounter some integration issues."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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)."
"The license is very expensive."
"The ease of use can be improved. When you are new it seems a bit complex."
"The visualization of the models is not very attractive, so the graphics should be improved."
"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."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The product must provide better integration with cloud-native technologies."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"Virtualization could be much better."
 

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."
"This solution is for large corporations because not everybody can afford it."
"The solution must improve its licensing models."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
26%
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.
842,592 professionals have used our research since 2012.