Dataiku vs SAS Enterprise Miner comparison

Dataiku and SAS are both solutions in the Data Science Platforms category. Dataiku is ranked #6 with an average rating of 8.2, while SAS is ranked #18 with an average rating of 9.0. Dataiku holds a 12.7% mindshare in Data Science Platforms, compared to SAS’s 0.7% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Dataiku

Read 12 Dataiku reviews

6,785 Views
5,638 Comparison Views

100% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

616 Views
474 Comparison Views

93% willing to recommend

Dataiku

SAS Enterprise Miner

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Executive SummaryUpdated on Dec 5, 2024

SAS Enterprise Miner and Dataiku compete in the data analytics and machine learning category. Dataiku holds an edge with its collaborative and intuitive workflow capabilities.

Features: SAS Enterprise Miner offers advanced statistical and predictive modeling, integration with SAS code for flexibility, and robust data processing capabilities. Dataiku provides a collaborative platform, visual data preparation tools, and compatibility with multiple data sources.

Room for Improvement: SAS Enterprise Miner could enhance user-friendliness and reduce its technical complexity. It would benefit from quicker deployment processes. Dataiku could improve its scalability for larger enterprise needs and offer deeper customization options. Further enhancement of machine learning algorithm options is also desirable.

Ease of Deployment and Customer Service: SAS Enterprise Miner has a steeper learning curve, often leading to longer deployment times but offers excellent technical support. Dataiku facilitates smoother deployment with a focus on user-friendly interfaces and provides comprehensive support and resources for seamless assistance.

Pricing and ROI: SAS Enterprise Miner generally requires a higher initial investment with training and implementation costs, affecting short-term ROI. Dataiku offers flexible pricing and is seen as providing better ROI due to lower setup costs and faster deployment, appealing to businesses seeking quick returns.

To learn more, read our detailed Dataiku vs. SAS Enterprise Miner Report (Updated: March 2025).

Buyer's Guide

Dataiku vs. SAS Enterprise Miner

March 2025

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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

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

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

Data Science Lead at a mining and metals company with 10,001+ employees

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.

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reviewer1447110

Senior Systems Engineer at a financial services firm with 10,001+ employees

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.

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Quotes from Members

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

Pros

"Cloud-based process run helps in not keeping the systems on while processes are running."

"One of the valuable features of Dataiku is the workflow capability."

"I believe the return on investment looks positive."

"Data Science Studio's data science model is very useful."

"I rate the overall product as eight out of ten."

"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."

"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."

"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."

More Dataiku pros

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

"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."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"The solution is very good for data mining or any mining issues."

"The solution is able to handle quite large amounts of data beautifully."

"Good data management and analytics."

"I like the way the product visually shows the data pipeline."

"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."

More SAS Enterprise Miner pros

Cons

"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."

"There is room for improvement in terms of allowing for more code-based features."

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."

"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

"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."

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

More Dataiku cons

"The ease of use can be improved. When you are new it seems a bit complex."

"The user interface of the solution needs improvement. It needs to be more visual."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

"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."

"Virtualization could be much better."

"The visualization of the models is not very attractive, so the graphics should be improved."

"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."

More SAS Enterprise Miner cons

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 must improve its licensing models."

"This solution is for large corporations because not everybody can afford it."

"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

17%

Educational Organization

14%

Manufacturing Company

Computer Software Company

Financial Services Firm

26%

University

12%

Educational Organization

Manufacturing Company

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.

See all answers

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...

See all answers

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.

See all answers

What do you like most about SAS Enterprise Miner?

I like the way the product visually shows the data pipeline.

See all answers

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...

See all answers

What needs improvement with SAS Enterprise Miner?

The product must provide better integration with cloud-native technologies.

See all answers

Comparisons

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Compared 33% of the time

KNIME vs Dataiku

Compared 18% of the time

Alteryx vs Dataiku

Compared 12% of the time

Altair RapidMiner vs Dataiku

Compared 11% of the time

Amazon SageMaker vs Dataiku

Compared 8% of the time

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SAS Visual Analytics vs SAS Enterprise Miner

Compared 34% of the time

KNIME vs SAS Enterprise Miner

Compared 25% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 24% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 17% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Dataiku

March 2025

Download Dataiku product report

Buyer's Guide

Data Mining

March 2025

Download SAS Enterprise Miner product report

Also Known As

Dataiku DSS

Enterprise Miner

Overview

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

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

Buyer's Guide

Dataiku vs. SAS Enterprise Miner

March 2025

Free Report: Dataiku vs. SAS Enterprise Miner

Find out what your peers are saying about Dataiku vs. SAS Enterprise Miner and other solutions. Updated: March 2025.

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