Databricks vs IBM SPSS Modeler comparison

Databricks and IBM are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.4, while IBM is ranked #13 with an average rating of 8.0. Databricks holds a 9.6% mindshare in Data Science Platforms, compared to IBM’s 3.7% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Databricks

Read 92 Databricks reviews

18,651 Views
8,020 Comparison Views

96% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,486 Views
1,790 Comparison Views

86% willing to recommend

Databricks

IBM SPSS Modeler

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and Databricks are data analytics competitors. Databricks has the upper hand due to its scalability and real-time processing for large-scale operations.

Features: IBM SPSS Modeler offers robust statistical tools, intuitive flowchart modeling, and effective predictive analytics. Databricks provides strong integration with big data technologies, advanced machine learning workflows, and collaboration through its notebook interface.

Room for Improvement: IBM SPSS Modeler could enhance its cloud capabilities and collaboration features. It may also benefit from more advanced machine learning tools. Databricks can improve by simplifying its initial adaptation to cloud environments, optimizing cost for smaller operations, and streamlining complex workflows for non-technical users.

Ease of Deployment and Customer Service: IBM SPSS Modeler is straightforward to deploy on-premise with minimal cloud infrastructure and offers attentive customer service. Databricks supports quick, cloud-native deployments with strong team collaboration but may require additional training for cloud acclimation.

Pricing and ROI: IBM SPSS Modeler generally presents lower initial setup costs with good ROI for small and mid-sized statistical analyses. Databricks, while involving higher upfront investment, often yields a higher long-term ROI through its scalability and big data capabilities, justifying the initial expense for extensive data operations.

To learn more, read our detailed Databricks vs. IBM SPSS Modeler Report (Updated: December 2025).

Buyer's Guide

Databricks vs. IBM SPSS Modeler

December 2025

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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

Databricks

Ranking in Data Science Platforms

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)

IBM SPSS Modeler

Ranking in Data Science Platforms

13th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Mining (3rd)

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Databricks is 9.6%, down from 18.9% compared to the previous year. The mindshare of IBM SPSS Modeler is 3.7%, up from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	9.6%
IBM SPSS Modeler	3.7%
Other	86.7%

Data Science Platforms

Featured Reviews

SimonRobinson

Governance And Engagement Lead

Improved data governance has enabled sensitive data tracking but cost management still needs work

I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.

Read full review

Prof. Dr. Rudolf Bisping

Business Owner at SASS GmbH

Support and flexibility enable effective project initiation and meet customer needs but deployment requires enhancement

The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a solution, and then I convert my MATLAB solution to C programming language. This I can deploy, and I can check it, and it is MISRA compatible. It is very easy to deploy it, to go from MATLAB to C or C++, which is actually needed in the car industry. In the car industry, they want to have it in the hardware. You cannot put MATLAB or IBM SPSS Modeler in the hardware of a car, but with C, there is no problem with a microcontroller. They can shoot it into the microcontroller, and I can check it with Polyspace, and it is MISRA compatible, which is an industrial standard. There is nothing similar in IBM SPSS Modeler. I made solutions with IBM SPSS Modeler, and then the customer said they wanted to make a production out of it, and it was not possible. I stopped with IBM SPSS Modeler 18. It is now 18.6 from what I know at the moment. I do not believe that there is a possibility to design a graphic user interface with it. It is itself a graphic user interface, where you put all sorts of little icons into the display.

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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

"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."

"It is fast, it's scalable, and it does the job it needs to do."

"It is a cost-effective solution."

"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."

"Databricks integrates well with other solutions."

"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."

"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."

"The solution offers a free community version."

More Databricks pros

"The supervised models are valuable. It is also very organized and easy to use."

"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."

"The quality is very good."

"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."

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

"Automation is great and this product is very organized."

"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."

"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"

More IBM SPSS Modeler pros

Cons

"It would be great if Databricks could integrate all the cloud platforms."

"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."

"Anyone who doesn't know SQL may find the product difficult to work with."

"I would love an integration in my desktop IDE. For now, I have to code on their webpage."

"While Databricks is generally a robust solution, I have noticed a limitation with debugging in the Delta Live Table, which could be improved."

"Can be improved by including drag-and-drop features."

"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."

"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."

More Databricks cons

"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."

"I would like see more programming languages added, like MATLAB. That would be better."

"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."

"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."

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

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

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

"The integration with sources and visualisation needs some improvement. The scalability needs improvement."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The pricing depends on the usage itself."

"Price-wise, I would rate Databricks a three out of five."

"Databricks are not costly when compared with other solutions' prices."

"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"There are different versions."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

More Databricks pricing and cost advice

"It is a huge increase to time savings."

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

"$5,000 annually."

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

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

"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."

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

"The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten users use the server with ten licenses, it runs faster. But if forty users use the same appliance, everything slows down. People then think it's not easy to do things and prefer using remote tools like Python to extract data from the database. It's not about being expensive or cheap, but about people's knowledge and experience in how to do the work."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

Healthcare Company

Government

12%

Financial Services Firm

12%

University

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	32

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

See all answers

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

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Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

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 budget. They used to encourage people to use the modeler for development. If ten us...

See all answers

What needs improvement with IBM SPSS Modeler?

See all answers

What is your primary use case for IBM SPSS Modeler?

I have been using IBM SPSS Modeler for a long time. I am using IBM SPSS Modeler mainly for ETL. Sometimes I use it to compare the results of the modeling as compared to MATLAB. MATLAB is the main t...

See all answers

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Product Reports

Buyer's Guide

Databricks

January 2026

Download Databricks product report

Buyer's Guide

IBM SPSS Modeler

January 2026

Download IBM SPSS Modeler product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

SPSS Modeler

Overview

Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.

Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.

What features make Databricks unique?

Notebook: Enables collaborative work among team members.
Delta Lake: Optimizes data management operations.
Unity Catalog: Provides governance over data assets.
Cloud Integration: Seamlessly connects with major cloud platforms.

What benefits can users expect from Databricks?

Versatility: Supports diverse applications in data science and engineering.
Performance: Delivers efficient handling of large-scale analytics tasks.
Collaboration: Enhances teamwork in data projects.
Unified Environment: Centralizes machine learning and analytics activities.

In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.

Databricks

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.

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

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https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

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

Databricks vs. IBM SPSS Modeler

December 2025

Free Report: Databricks vs. IBM SPSS Modeler

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