Dataiku vs TIBCO Data Science comparison

Dataiku and TIBCO are both solutions in the Data Science Platforms category. Dataiku is ranked #4 with an average rating of 8.0, while TIBCO is ranked #26. Dataiku holds a 6.7% mindshare in Data Science Platforms, compared to TIBCO’s 1.5% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Dataiku

Read 20 Dataiku reviews

5,913 Views
5,795 Comparison Views

100% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

822 Views
814 Comparison Views

100% willing to recommend

Dataiku

TIBCO Data Science

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

TIBCO Data Science and Dataiku are competing products in the data science platform market. Dataiku seems to have the upper hand due to its superior features and integration capabilities.

Features: TIBCO Data Science offers model management, visual analytics, and flexible deployment options, attracting those focused on comprehensive insights and budget constraints. Dataiku excels in collaborative data preparation, extensive integration, and robust support for AI projects, catering to organizations prioritizing teamwork and scalability.

Room for Improvement: TIBCO Data Science could enhance collaboration features, improve integration with third-party tools, and streamline user interface design to increase accessibility. Dataiku might focus on reducing costs, offering more customizable deployment options, and expanding customer support channels to enhance user satisfaction.

Ease of Deployment and Customer Service: TIBCO Data Science provides responsive support with both on-premise and cloud deployment, ideal for tailored solutions. Dataiku emphasizes easy cloud-based deployment with proactive customer service, making it user-friendly and scalable.

Pricing and ROI: TIBCO Data Science presents cost-effective solutions with competitive pricing models, appealing to budget-conscious businesses. Dataiku's higher costs are offset by substantial ROI from enhanced productivity, drawing organizations focused on maximizing returns on their data investments.

To learn more, read our detailed Dataiku vs. TIBCO Data Science Report (Updated: March 2026).

Buyer's Guide

Dataiku vs. TIBCO Data Science

March 2026

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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

8.2

Reviews Sentiment

6.5

Number of Reviews

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

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. The mindshare of TIBCO Data Science is 1.5%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	6.7%
TIBCO Data Science	1.5%
Other	91.8%

Data Science Platforms

Featured Reviews

Shubhamkumar Gomar

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.

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JacekSierajewski

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.

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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

"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."

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

"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."

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

"I believe the return on investment looks positive."

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

"The most valuable feature is the set of visual data preparation tools."

More Dataiku pros

"The most valuable feature is the performance."

"The idea that you don't have to generate reports each day but they are sent automatically is great."

"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 most valuable feature is the ease of setting up visualizations."

Cons

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."

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

"The ability to have charts right from the explorer would be an improvement."

"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."

"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 have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."

"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."

More Dataiku cons

"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."

"I would like the visualization for the map of countries to be more easily configurable."

"The scripting for customization could be improved."

"Additional templates would help to get things moving more quickly in terms of getting the reports out."

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

18%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities Company

Comms Service Provider

22%

Manufacturing Company

14%

Performing Arts

Transportation Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	13

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.

See all answers

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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Also Known As

Dataiku DSS

Alpine Data Chorus

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

TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.

TIBCO

Sample Customers

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

Havas Media, Tipping Point Community, eviCore

Buyer's Guide

Dataiku vs. TIBCO Data Science

March 2026

Free Report: Dataiku vs. TIBCO Data Science

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