Dataiku vs SAP Predictive Analytics comparison

Dataiku and SAP are both solutions in the Data Science Platforms category. Dataiku is ranked #4 with an average rating of 8.0, while SAP is ranked #28. Dataiku holds a 7.1% mindshare in Data Science Platforms, compared to SAP’s 1.2% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

Dataiku

Read 17 Dataiku reviews

5,767 Views
5,652 Comparison Views

100% willing to recommend

SAP Predictive Analytics

Read 3 SAP Predictive Analytics reviews

559 Views
559 Comparison Views

100% willing to recommend

Dataiku

SAP Predictive Analytics

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Executive SummaryUpdated on Dec 5, 2024

SAP Predictive Analytics and Dataiku compete in predictive modeling and data analysis. Dataiku is perceived to have an edge in features, making it seem worth its cost.

Features: SAP Predictive Analytics automates predictive model creation and integrates with other SAP tools. Dataiku offers a user-friendly platform with extensive machine learning functionalities and collaboration tools, enhancing team productivity. Dataiku's comprehensive feature set provides an advantage over SAP Predictive Analytics.

Ease of Deployment and Customer Service: Dataiku offers a simple, flexible deployment model that facilitates implementation across diverse environments. SAP Predictive Analytics may have a more complex setup but benefits from extensive support within the SAP ecosystem. Both provide solid customer service, but Dataiku's straightforward deployment approach is more favorable.

Pricing and ROI: SAP Predictive Analytics often has lower initial setup costs due to its integration with existing SAP systems, leading to faster ROI. Dataiku might have a higher upfront cost but offers significant long-term value through extensive features and scalability options, resulting in better ROI for complex analytics needs.

To learn more, read our detailed Dataiku vs. SAP Predictive Analytics Report (Updated: December 2025).

Buyer's Guide

Dataiku vs. SAP Predictive Analytics

December 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

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

SAP Predictive Analytics

Ranking in Data Science Platforms

28th

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of Dataiku is 7.1%, down from 12.4% compared to the previous year. The mindshare of SAP Predictive Analytics is 1.2%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Dataiku	7.1%
SAP Predictive Analytics	1.2%
Other	91.7%

Data Science Platforms

Featured Reviews

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

Unified platform has accelerated model development and improved collaborative data science work

I think Dataiku could be improved or enhanced in future releases with more 'talk to my data' capabilities, maybe more NLP features, and maybe a platform to build agents. These improvements would benefit me and my processes because they will help us to continue using Dataiku as one platform; right now we are exploring other platforms for the features which are missing, and if they are available within the same platform, I think it will increase the usage of Dataiku further. I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well.

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Gary Cook

Executive at Empowered Analytics

Enables us to forecast and pull trends and has an easy installation

My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

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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

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"Our clients can easily drag and drop components and use them on the spot."

"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."

"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 consider the return on investment with Dataiku valuable because for us, it is one single platform where all our data scientists come together and work on any model building, so it is collaboration, plus having everything in one place, organized, having proper project management, and then built-in capabilities which help to facilitate model building."

"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."

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

"Dataiku is a complete platform to build ETL and data pipeline and deploy it, which I appreciate."

More Dataiku pros

"The most valuable features are the analytics and reporting."

"I think the features of the actual ability to forecast and pull trends and correlations has been really good."

Cons

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

"I think it would help if Data Science Studio added some more features and improved the data model."

"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."

"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."

"I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well."

"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."

"We still encounter some integration issues."

More Dataiku cons

"This solution works for acquired data but not live, real-time data."

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."

"A free trial version is available for testing out this solution."

"The pricing is reasonable"

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

Manufacturing Company

Energy/Utilities Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	11

No data available

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

I am not the person involved in the process regarding pricing, setup cost, and licensing.

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What needs improvement with Dataiku Data Science Studio?

To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...

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What is your primary use case for Dataiku Data Science Studio?

My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...

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Product Reports

Buyer's Guide

Dataiku

January 2026

Download Dataiku product report

Buyer's Guide

Data Science Platforms

January 2026

Download SAP Predictive Analytics product report

Also Known As

Dataiku DSS

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

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

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

SAP

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

mBank

Buyer's Guide

Dataiku vs. SAP Predictive Analytics

December 2025

Free Report: Dataiku vs. SAP Predictive Analytics

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