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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 July 2026, in the Data Science Platforms category, the mindshare of Dataiku is 5.1%, down from 13.1% compared to the previous year. The mindshare of TIBCO Data Science is 1.5%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Dataiku5.1%
TIBCO Data Science1.5%
Other93.4%
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

"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."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"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."
"The best features Dataiku offers that help me with my demand forecasting and data science projects include having a complete overview of the flow directly from the flowchart, allowing me to observe all the steps in a single overview, and the ability to use a no-code, low-code node."
"Technical support is really, really good."
"Our clients can easily drag and drop components and use them on the spot."
"Data Science Studio's data science model is very useful."
"Dataiku has positively impacted my organization as most of our projects have been migrated to Dataiku, and now people are relying on it as a go-to tool for all our data use cases."
"In general, I would say that this is a good tool and I recommend it."
"The most valuable feature is the ease of setting up visualizations."
"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."
"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."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
 

Cons

"I think it would help if Data Science Studio added some more features and improved the data model."
"The license is very expensive."
"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."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."
"The ability to have charts right from the explorer would be an improvement."
"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."
"I need to stress upon the part about customer support because there are some product issues we have identified and raised with customer support, but sometimes the response is delayed, so that can be improved."
"The scripting for customization could be improved."
"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 initial setup was quite complex."
"I would like the visualization for the map of countries to be more easily configurable."
"At this point, there are other tools that I would recommend before using Spotfire."
 

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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
6%
Comms Service Provider
16%
Construction Company
15%
Financial Services Firm
11%
Manufacturing Company
10%
 

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: June 2026.
903,933 professionals have used our research since 2012.