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 8.3, while IBM is ranked #19 with an average rating of 7.0. Databricks holds a 15.3% mindshare in Data Science Platforms, compared to IBM’s 2.6% 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

23,965 Views
10,784 Comparison Views

96% willing to recommend

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

2,195 Views
1,449 Comparison Views

86% willing to recommend

Databricks

IBM SPSS Modeler

Comparison Buyer's Guide

Download the report

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: July 2025).

Buyer's Guide

Databricks vs. IBM SPSS Modeler

July 2025

Download the complete report

Helped 865,295 peers since 2012

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 (8th), Streaming Analytics (1st)

IBM SPSS Modeler

Ranking in Data Science Platforms

19th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Mining (4th)

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of Databricks is 15.3%, down from 19.8% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.6%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

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

"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."

"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."

"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."

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

"The integration with Python and the notebooks really helps."

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

"Databricks is a robust solution for big data processing, offering flexibility and powerful features."

"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."

More Databricks pros

"It will scale up to anything we need."

"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."

"It is very scalable for non-technical people."

"So far, the stability has been rock solid."

"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."

"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."

"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."

"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."

More IBM SPSS Modeler pros

Cons

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

"It's not easy to use, and they need a better UI."

"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."

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

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

"There would also be benefits if more options were available for workers, or the clusters of the two points."

"Would be helpful to have additional licensing options."

"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."

More Databricks cons

"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."

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

"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."

"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."

"Unstructured data is not appropriate for SPSS Modeler."

"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."

"The challenge for the very technical data scientists: It is constraining for them."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."

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

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

"I rate the price of Databricks as eight out of ten."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"The pricing depends on the usage itself."

"The solution is a good value for batch processing and huge workloads."

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."

More Databricks pricing and cost advice

"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."

"$5,000 annually."

"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."

"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."

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

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

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

More IBM SPSS Modeler pricing and cost advice

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

865,295 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Financial Services Firm

12%

Educational Organization

11%

Government

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

See all answers

Comparisons

Dataiku vs Databricks

Compared 10% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau Enterprise vs Databricks

Compared 5% of the time

More Databricks Competitors

Microsoft Power BI vs IBM SPSS Modeler

Compared 24% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 24% of the time

KNIME Business Hub vs IBM SPSS Modeler

Compared 14% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

Dataiku vs IBM SPSS Modeler

Compared 3% of the time

More IBM SPSS Modeler Competitors

Product Reports

Buyer's Guide

Databricks

August 2025

Download Databricks product report

Buyer's Guide

IBM SPSS Modeler

August 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

July 2025

Free Report: Databricks vs. IBM SPSS Modeler

Find out what your peers are saying about Databricks vs. IBM SPSS Modeler and other solutions. Updated: July 2025.

DOWNLOAD NOW

865,295 professionals have used our research since 2012.

See our Databricks vs. IBM SPSS Modeler 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.