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Dataiku vs TIBCO Data Science 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
2nd
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
21
Ranking in other categories
No ranking in other categories
TIBCO Data Science
Ranking in Data Science Platforms
26th
Average Rating
7.6
Reviews Sentiment
6.3
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of Dataiku is 5.6%, down from 12.8% compared to the previous year. The mindshare of TIBCO Data Science is 1.6%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dataiku5.6%
TIBCO Data Science1.6%
Other92.8%
Data Science Platforms
 

Featured Reviews

SK
Senior Data Scientist at Deloitte
Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly
In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.
JS
Tibco Spotfire Expert (contractor via Amaris) at GSK
Good performance, reporting, and data visualization
The two similar solutions that I have used are MicroStrategy and Tableau. Tableau is pretty similar and it would be difficult for me to point out the differences. With MicroStrategy, it has a great feature where you build the representation in the database and it then the tool creates SQL queries by itself. There are more differences between these tools but this is the one essential difference.

Quotes from Members

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

Pros

"Using Dataiku has meant that we spend less time on preparing and cleaning data, and we spend less time on blending models together, ultimately meaning that we can spend more time modeling."
"The best features Dataiku offers include the ability for users to use the node without having to code and the functionality related to low-code/no-code."
"Compared to Informatica, this tool is extremely easy with its GUI-based functionality and large compatibility with various data sources, and maintenance processes are much more automated than ever, with fewer errors."
"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"I believe the return on investment looks positive."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The solution is quite stable."
"Data Science Studio's data science model is very useful."
"In this sector of the market, it is indeed a better tool than the other data analytics tool, such as QlikView, for example."
"The most valuable feature is the performance."
"In general, I would say that this is a good tool and I recommend it."
"We like the way we can drill down into each report to get back data on each project, and from the portfolio level I can see what is happening on it, including indirect costs hitting each CIO portfolio and actual resources in terms of time as well as cost."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"The most valuable feature is the ease of setting up visualizations."
"The most valuable feature is the ease of setting up visualizations."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
 

Cons

"There is room for improvement in terms of allowing for more code-based features."
"I would like to have better exclusion of data capability."
"Dataiku is down a lot of times, and we have to wait for sometimes five, ten, or fifteen minutes, after which it gets working again, and during those times, we are unable to get our work done."
"I think it would help if Data Science Studio added some more features and improved the data model."
"The ability to have charts right from the explorer would be an improvement."
"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."
"We still encounter some integration issues."
"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."
"I would like the visualization for the map of countries to be more easily configurable."
"The initial setup was quite complex."
"Whenever the client or someone was opening the report it would take around 15 to 20 minutes to open the first time."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
"The scripting for customization could be improved."
"At this point, there are other tools that I would recommend before using Spotfire."
"The scripting for customization could be improved."
 

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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Manufacturing Company
9%
Computer Software Company
9%
Energy/Utilities Company
6%
Comms Service Provider
16%
Construction Company
15%
Manufacturing Company
11%
Financial Services Firm
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise2
Large Enterprise13
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
The licenses are a bit high for companies that are still hesitating to get started with using Dataiku. For my personal projects, I used the thirty-day free trial. Regarding my company, I did not ha...
What needs improvement with Dataiku Data Science Studio?
I have no suggestions for improvements because it's all good; it just sometimes lags a lot, and I don't know if the server is full or what, but it sometimes takes a lot of time while loading and re...
What is your primary use case for Dataiku Data Science Studio?
My main use case for Dataiku involves ETL pipelines, mainly for data analysis, and I majorly use SQL queries for that. For ETL pipelines and data analysis, I had to create the output by combining a...
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Also Known As

Dataiku DSS
Alpine Data Chorus
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
Havas Media, Tipping Point Community, eviCore
Find out what your peers are saying about Dataiku vs. TIBCO Data Science and other solutions. Updated: April 2026.
893,221 professionals have used our research since 2012.