Dataiku vs TIBCO Data Science comparison

Dataiku and TIBCO are both solutions in the Data Science Platforms category. Dataiku is ranked #7 with an average rating of 7.5, while TIBCO is ranked #24. Dataiku holds a 11.8% mindshare in Data Science Platforms, compared to TIBCO’s 0.5% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Comparison Buyer's Guide

Download the report

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: December 2024).

Buyer's Guide

Dataiku vs. TIBCO Data Science

December 2024

Download the complete report

Helped 824,067 peers since 2012

Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of December 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.7%, up from 2.7% compared to the previous year. The mindshare of Dataiku is 11.8%, up from 7.6% compared to the previous year. The mindshare of TIBCO Data Science is 0.5%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts

I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.

Read full review

Sabrine Bendimerad

Data Scientist at Electricite De France

Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.

Read full review

Veeresh-SHRINGARI

Portfolio Manager, AI & ML at a healthcare company with 10,001+ employees

A straightforward initial setup and good reporting but needs better documentation

It would be ideal if it could be put onto the NMP where you can make more of an analysis. Right now, people don't have enough time to go through the report and make an analysis. It should provide the information of what is on the report into some kind of a dialogue form. Then, a person can ask certain questions and it could interactively give the required report. 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. If you are doing certain operations of RDBMS, you suffer in terms of the latency of the data. That can be improved upon. Users should be able to cross tables of the web pages they are developing on Spotfire and this needs to be really easy and convenient. Right now, you need to do a lot of tweaks. The solution should be more user-friendly and require fewer tweaks, extensions, and workarounds.

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

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."

"It offers very good visualization."

"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

"It is perfectly adequate if all you need are the results and not the trail of evidence."

More IBM SPSS Statistics pros

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

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

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

"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."

"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."

"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 solution is quite stable."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

More Dataiku pros

"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."

"The most valuable feature is the performance."

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

Cons

"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."

"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."

"The design of the experience can be improved."

"The statistics should be more self-explanatory with detailed automated reports."

"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."

"It could allow adding color to data models to make them easier to interpret."

"The reports could be better."

"In some cases, the product takes time to load a large dataset. They could improve this particular area."

More IBM SPSS Statistics 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 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."

"I think it would help if Data Science Studio added some more features and improved the data model."

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

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

"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."

"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."

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."

"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."

Pricing and Cost Advice

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

"We think that IBM SPSS is expensive for this function."

"It's quite expensive, but they do a special deal for universities."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"I rate the tool's pricing a five out of ten."

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

More IBM SPSS Statistics 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

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

824,067 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

Financial Services Firm

18%

Educational Organization

16%

Manufacturing Company

Computer Software Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Statistics?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

See all answers

What needs improvement with IBM SPSS Statistics?

IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...

See all answers

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

It is very expensive.

See all answers

What needs improvement with Dataiku Data Science Studio?

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integratin...

See all answers

What is your primary use case for Dataiku Data Science Studio?

We use the solution for data science and machine learning.

See all answers

Ask a question

Earn 20 points

Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 16% of the time

Alteryx vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 11% of the time

KNIME vs IBM SPSS Statistics

Compared 2% of the time

More IBM SPSS Statistics Competitors

Databricks vs Dataiku

Compared 37% of the time

KNIME vs Dataiku

Compared 15% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 11% of the time

IBM SPSS Modeler vs Dataiku

Compared 1% of the time

More Dataiku Competitors

TIBCO Statistica vs TIBCO Data Science

Compared 38% of the time

Amazon SageMaker vs TIBCO Data Science

Compared 36% of the time

More TIBCO Data Science Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Dataiku

December 2024

Download Dataiku product report

Buyer's Guide

Data Science Platforms

December 2024

Download TIBCO Data Science product report

Also Known As

SPSS Statistics

Dataiku DSS

Alpine Data Chorus

Learn More

Video not available

IBM

Dataiku

TIBCO

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

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.

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.

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

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

Havas Media, Tipping Point Community, eviCore

Buyer's Guide

Dataiku vs. TIBCO Data Science

December 2024

Free Report: Dataiku vs. TIBCO Data Science

Find out what your peers are saying about Dataiku vs. TIBCO Data Science and other solutions. Updated: December 2024.

DOWNLOAD NOW

824,067 professionals have used our research since 2012.

See our Dataiku vs. TIBCO Data Science report.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.