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Alteryx vs Dataiku 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

Alteryx
Ranking in Data Science Platforms
5th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
81
Ranking in other categories
Predictive Analytics (1st), Data Preparation Tools (1st)
Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.0
Reviews Sentiment
7.2
Number of Reviews
9
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2025, in the Data Science Platforms category, the mindshare of Alteryx is 6.7%, down from 8.3% compared to the previous year. The mindshare of Dataiku is 12.1%, up from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Theresa McLaughlin - PeerSpot reviewer
Quick development enables seamless data processing despite occasional support issues
There were times when the product would fail during development without an apparent reason. The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system. Licensing negotiations were problematic, affecting our product usage. For instance, our licenses were temporarily lost during negotiations when an agreement couldn't be reached.
Sabrine Bendimerad - PeerSpot reviewer
Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.

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 for me is integration."
"The scheduling feature for the automation is excellent."
"I like that I can merge data from different sources into one place."
"The solution offers excellent predicting power. The accuracy and confidence have been great."
"The initial setup is easy."
"The tools are built-in. You just plug and play, drag and drop, once you understand how to use the tools, it is easy."
"It offered quick development, with the ability to process large datasets."
"The solution has a very strong community that is involved in the product. It helps make the usage easier and helps us find answers to our questions."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Data Science Studio's data science model is very useful."
"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."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"I rate the overall product as eight out of ten."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"The most valuable feature is the set of visual data preparation tools."
 

Cons

"The only area where the product lags is documentation and videos on the analytical app and the batch macro."
"Licensing negotiations were problematic, affecting our product usage."
"It is a little bit pricey."
"Sometimes workflows tend to queue up, and they tend to get canceled for some reason that we don't know sometimes."
"The interface could be improved."
"All of the reports are migrated or exported in an Excel file, and most of the time, a business intelligence tool is required. They could have better reporting. The aesthetic could be improved."
"The principal problem is the pricing. They're expensive products."
"Its most valuable feature lies in its functionality."
"I think it would help if Data Science Studio added some more features and improved the data model."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"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."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"The ability to have charts right from the explorer would be an improvement."
"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
 

Pricing and Cost Advice

"ROI is huge. There are some secondary benefits, like analysts getting their post 5 PM time back or the ability to shorten all closing processes to a half or less."
"The designer license costs 5000 euros. The server edition is 1000 euros."
"We have a yearly cost that we pay for the licensing. We do not pay any costs in addition to the licensing fees."
"There is a license required for this solution."
"Alteryx isn't extortionately expensive, but it's not cheap either."
"I rate the tool's pricing a two out of ten."
"The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area."
"We use the free version of the solution. There are enterprise licenses available. It cost approximately $5,000 annually. It is an expensive solution and there are additional features that cost more money."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Manufacturing Company
10%
Computer Software Company
9%
Healthcare Company
6%
Financial Services Firm
18%
Educational Organization
16%
Manufacturing Company
9%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
One of the differences is that with Alteryx you can use it as an ETL and analytics tool. Please connect with me directly if you want to know more.
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, R integrations if your team requires this. It can handle over 2 billion rows of...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products. Regarding Alteryx I can say the following: - An excellent desktop tool for Data Prep and analytics. - Featu...
What needs improvement with Dataiku Data Science Studio?
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to us...
What is your primary use case for Dataiku Data Science Studio?
We use the solution for data science and machine learning.
 

Comparisons

 

Also Known As

No data available
Dataiku DSS
 

Learn More

 

Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Find out what your peers are saying about Alteryx vs. Dataiku and other solutions. Updated: December 2024.
831,071 professionals have used our research since 2012.