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 #16 with an average rating of 7.5. Databricks holds a 13.9% mindshare in Data Science Platforms, compared to IBM’s 3.5% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Databricks

Read 91 Databricks reviews

20,775 Views
8,933 Comparison Views

96% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,258 Views
1,558 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: September 2025).

Buyer's Guide

Databricks vs. IBM SPSS Modeler

September 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), Streaming Analytics (1st)

IBM SPSS Modeler

Ranking in Data Science Platforms

16th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Mining (3rd)

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Databricks is 13.9%, down from 19.2% compared to the previous year. The mindshare of IBM SPSS Modeler is 3.5%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	13.9%
IBM SPSS Modeler	3.5%
Other	82.6%

Data Science Platforms

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

Read full review

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.

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 built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."

"I work in the data science field and I found Databricks to be very useful."

"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"

"Databricks is a scalable solution. It is the largest advantage of the solution."

"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."

"Databricks helps crunch petabytes of data in a very short period of time."

"Databricks' capability to process data in parallel enhances data processing speed."

"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."

More Databricks pros

"We have full control of the data handling process."

"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."

"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."

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

"Automated modelling, classification, or clustering are very useful."

"We are using it either for workforce deployment or to improve our operations."

"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."

More IBM SPSS Modeler pros

Cons

"The product cannot be integrated with a popular coding IDE."

"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."

"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."

"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."

"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."

"Would be helpful to have additional licensing options."

"There is room for improvement in the documentation of processes and how it works."

"There should be better integration with other platforms."

More Databricks cons

"Dimension reduction should be classified separately."

"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."

"Customer support is hard to contact."

"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."

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

"It would be good if IBM added help resources to the interface."

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

"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The pricing depends on the usage itself."

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

"The billing of Databricks can be difficult and should improve."

"The product pricing is moderate."

"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."

"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."

"It is an expensive tool. The licensing model is a pay-as-you-go one."

"We only pay for the Azure compute behind the solution."

More Databricks pricing and cost advice

"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."

"$5,000 annually."

"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."

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

"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."

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

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

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

Manufacturing Company

Healthcare Company

Financial Services Firm

12%

Educational Organization

11%

Government

10%

University

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...

See all answers

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 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 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?

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 ...

See all answers

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Compared 10% of the time

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Compared 1% of the time

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Product Reports

Buyer's Guide

Databricks

September 2025

Download Databricks product report

Buyer's Guide

IBM SPSS Modeler

September 2025

Download IBM SPSS Modeler product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

SPSS Modeler

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

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

Sign up for the trial
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

September 2025

Free Report: Databricks vs. IBM SPSS Modeler

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