Dataiku vs IBM SPSS Modeler comparison

Dataiku and IBM are both solutions in the Data Science Platforms category. Dataiku is ranked #7 with an average rating of 7.5, while IBM is ranked #13 with an average rating of 7.0. Dataiku holds a 11.8% mindshare in Data Science Platforms, compared to IBM’s 2.5% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and Dataiku are leading tools in data analysis and modeling. Dataiku is often preferred for its comprehensive features that many users feel justify the higher cost.

Features:IBM SPSS Modeler excels in predictive modeling, statistical analysis, and integration with IBM's ecosystem. It offers robust visual programming capabilities and combines different techniques like regression and neural networks in one node. Dataiku stands out with its collaborative data science platform, extensive machine learning tools, and easy integration with diverse data environments. It provides advanced data preparation and supports code from languages like Python and R.

Room for Improvement:IBM SPSS Modeler's visual modeling is less advanced than other software solutions, and its integration for governance and security needs to be enhanced. It's complex to use for beginners without data science expertise. Dataiku could improve its cost efficiency as the perceived value often comes with a steep price. Its user interface, while comprehensive, can be overwhelming for new users, and some users feel the automation of certain tasks could be further developed to enhance usability.

Ease of Deployment and Customer Service:IBM SPSS Modeler provides a structured deployment process with support from IBM’s network, which some users find rigid. Dataiku offers a flexible deployment model, favoring seamless integration and iterative updates, coupled with a responsive support team that provides personalized attention.

Pricing and ROI:IBM SPSS Modeler involves a higher initial setup cost due to its enterprise-grade features, promising long-term value with an emphasis on advanced analytics. Dataiku presents a scalable pricing structure, appealing to businesses seeking flexible data solutions. Both offer valuable returns, with IBM focusing on comprehensive analytics and Dataiku on flexibility and scalability.

To learn more, read our detailed Dataiku vs. IBM SPSS Modeler Report (Updated: December 2024).

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

December 2024

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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 IBM SPSS Modeler is 2.5%, down from 2.8% 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.

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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.

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PeterHuo

Application Architect at Canada Border Services Agency

Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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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

"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."

"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."

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

"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."

"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."

"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."

"It has the ability to easily change any variable in our research."

"One feature I found very valuable was the analysis of variance (ANOVA)."

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 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."

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

"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

"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."

"The visual modeling capability is one of its attractive features."

"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."

"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."

"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."

"Some basic form of feature engineering for classification models. This really quickens the model development process."

"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."

"We use analytics with the visual modeling capability to leverage productivity improvements."

More IBM SPSS Modeler pros

Cons

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

"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."

"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."

"It could provide even more in the way of automation as there are many opportunities."

"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."

More IBM SPSS Statistics cons

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

"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."

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

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

More Dataiku cons

"Dimension reduction should be classified separately."

"The platform's cloud version needs improvements."

"It's not as user friendly as it could be."

"There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database."

"The product does not have a search function for tags."

"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."

"We have run into a few problems doing some entity matching/analytics."

"The standard package (personal) is not supported for database connection."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The price of this solution is a little bit high, which was a problem for my company."

"More affordable training for new staff members."

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

"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."

"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."

"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."

"The price of IBM SPSS Statistics could improve."

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."

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"This tool, being an IBM product, is pretty expensive."

"It is a huge increase to time savings."

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."

"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."

"It got us a good amount of money with quick and efficient modeling."

"It is an expensive product."

"$5,000 annually."

More IBM SPSS Modeler pricing and cost advice

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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

Educational Organization

13%

Financial Services Firm

13%

Computer Software Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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.

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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...

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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...

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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

What do you like most about IBM SPSS Modeler?

Compared to other tools, the product works much easier to analyze data without coding.

See all answers

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

The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly bud...

See all answers

What needs improvement with IBM SPSS Modeler?

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the ser...

See all answers

Comparisons

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Weka vs IBM SPSS Statistics

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KNIME vs IBM SPSS Statistics

Compared 3% of the time

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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

Starburst Galaxy vs Dataiku

Compared 1% of the time

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Microsoft Power BI vs IBM SPSS Modeler

Compared 28% of the time

KNIME vs IBM SPSS Modeler

Compared 14% of the time

RapidMiner vs IBM SPSS Modeler

Compared 8% of the time

Alteryx vs IBM SPSS Modeler

Compared 7% of the time

IBM Watson Studio vs IBM SPSS Modeler

Compared 2% of the time

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Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Dataiku

December 2024

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Buyer's Guide

IBM SPSS Modeler

December 2024

Download IBM SPSS Modeler product report

Also Known As

SPSS Statistics

Dataiku DSS

SPSS Modeler

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Dataiku

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IBM

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.

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

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https://www.ibm.com/products/spss-modeler/pricing

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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

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

December 2024

Free Report: Dataiku vs. IBM SPSS Modeler

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