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 5.9% 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 21 Dataiku reviews

6,404 Views
6,276 Comparison Views

100% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

980 Views
970 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

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 April 2026, in the Data Science Platforms category, the mindshare of Dataiku is 5.9%, down from 12.7% 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	5.9%
TIBCO Data Science	1.5%
Other	92.6%

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

"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."

"Cloud-based process run helps in not keeping the systems on while processes are running."

"Dataiku has positively impacted my organization, specifically in one project where we performed migration from AWS to Dataiku, speeding up the solution by close to 40% and reducing architecture costs by almost 70%, which was a significant benefit and greatly impacted our operations."

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

"I like the interface, which is probably my favorite part of the solution; it is really user-friendly, colorful, and I think it is really beautiful and well-designed."

"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."

More Dataiku pros

"In this sector of the market, it is indeed a better tool than the other data analytics tool, such as QlikView, for example."

"In general, I would say that this is a good tool and I recommend it."

"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 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."

Cons

"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."

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

"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 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."

"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."

"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."

"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."

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."

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

"The scripting for customization could be improved."

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

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

"The initial setup was quite complex."

"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."

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 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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