Dataiku vs TIBCO Data Science comparison

Dataiku and TIBCO are both solutions in the Data Science Platforms category. Dataiku is ranked #2 with an average rating of 8.1, while TIBCO is ranked #26. Dataiku holds a 5.6% mindshare in Data Science Platforms, compared to TIBCO’s 1.6% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Dataiku

Read 21 Dataiku reviews

6,883 Views
6,745 Comparison Views

100% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

1,097 Views
1,086 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: April 2026).

Buyer's Guide

Dataiku vs. TIBCO Data Science

April 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

2nd

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 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
Product	Mindshare (%)
Dataiku	5.6%
TIBCO Data Science	1.6%
Other	92.8%

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.

Read full review

Quotes from Members

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

Pros

"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."

"The solution is quite stable."

"Technical support is really, really good."

"The best feature in Dataiku is that once the data is connected in the underneath layer, it flows exceptionally smoothly if you know how to tweak it."

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

"Dataiku has positively impacted my organization since we use it majorly for our day-to-day work, and it is very helpful in creating and managing ETL pipelines to create a project flow, making it easy to go back to any step and then make edits if some changes occur."

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

More Dataiku pros

"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."

"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, 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."

"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

"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 find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete."

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."

"Dataiku's scalability is not one of the best solutions to scale."

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

"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."

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

More Dataiku cons

"The scripting for customization could be improved."

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

"The initial setup was quite complex."

"At this point, there are other tools that I would recommend before using Spotfire."

"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."

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

Computer Software Company

Energy/Utilities Company

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 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?

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...

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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...

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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...

See all answers

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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 Data Science enables organizations to harness data-driven insights through unified analytics and machine learning capabilities. It empowers users to accelerate decision-making by simplifying complex data processes.

TIBCO Data Science provides a comprehensive platform for building, deploying, and managing machine learning models on a large scale. It facilitates collaborative efforts between data scientists and business experts, promoting innovation. The integration with various data sources helps streamline predictive analytics processes, ensuring accessibility and efficiency.

What are the key features of TIBCO Data Science?

Model Management: Efficiently manage and govern machine learning models across their lifecycle.
Data Preparation: Easily prepare data with intuitive tools that clean and enrich datasets.
Collaboration: Enhance team collaboration with built-in tools for sharing insights and models.
Scalability: Seamlessly scale data operations to handle large datasets and complex algorithms.

What benefits should be considered when evaluating TIBCO Data Science?

Improved Decision-Making: Provides actionable insights that drive informed decisions.
Cost Efficiency: Reduces operational costs through streamlined data processing.
Enhanced Productivity: Boosts productivity by automating data tasks.
ROI Growth: Offers potential for significant return on investment through better data utilization.

TIBCO Data Science finds significant applications across various industries. In finance, it aids in risk management and fraud detection. In healthcare, it supports predictive analytics for better patient outcomes. Retailers leverage its capabilities for personalized marketing and supply chain optimization. Manufacturing industries utilize its tools to enhance operational efficiency and predictive maintenance strategies.

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

April 2026

Free Report: Dataiku vs. TIBCO Data Science

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