IBM SPSS Modeler vs Starburst Galaxy comparison

Why PeerSpot?

IBM and Starburst are both solutions in the Data Science Platforms category. IBM is ranked #13 with an average rating of 9.0, while Starburst is ranked #7 with an average rating of 9.3. IBM holds a 3.2% mindshare in Data Science Platforms, compared to Starburst’s 1.5% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

IBM SPSS Modeler

Read 40 IBM SPSS Modeler reviews

4,816 Views
3,708 Comparison Views

86% willing to recommend

Starburst Galaxy

Read 12 Starburst Galaxy reviews

2,242 Views
1,726 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Starburst Galaxy

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between IBM SPSS Modeler and Starburst Galaxy based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed IBM SPSS Modeler vs. Starburst Galaxy Report (Updated: September 2026).

Buyer's Guide

IBM SPSS Modeler vs. Starburst Galaxy

September 2026

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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

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)

Starburst Galaxy

Ranking in Data Science Platforms

7th

Average Rating

9.4

Reviews Sentiment

2.6

Number of Reviews

Ranking in other categories

Streaming Analytics (8th)

Mindshare comparison

As of October 2026, in the Data Science Platforms category, the mindshare of IBM SPSS Modeler is 3.2%, down from 3.5% compared to the previous year. The mindshare of Starburst Galaxy is 1.5%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Starburst Galaxy	1.5%
IBM SPSS Modeler	3.2%
Other	95.3%

Data Science Platforms

Featured Reviews

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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Pedromachado Ventura

Data Analyst at a financial services firm with 5,001-10,000 employees

Unified SQL layer has streamlined access to distributed historical data for analytics and reporting

One area that I think could be improved is the experience when performance issues occur. When a query is slow, it is not always immediately obvious to me whether the bottleneck comes from Starburst Galaxy itself, the underlying data source, the query design, or the reporting tool. Better visibility into query performance and easier diagnostics for non-administrators would be useful. Another potential improvement would be enhancing the experience with BI tools to make it more seamless. I work a lot with Power BI, and when you are working with larger data sets, performance can sometimes depend on several different layers. Having more visibility into what is happening between the BI tool, Starburst Galaxy, and the underlying source would be helpful. I also think onboarding could be a little more accessible for analysts. There is good technical documentation, but sometimes I just need to understand the best way to approach a common use case without diving too deep into the platform architecture. The main improvement would be troubleshooting. I have not used the AI capabilities extensively, so I cannot give a detailed assessment. I am not sure if my organization has the full capabilities of Starburst Galaxy, but I think adding AI on top of the data layer is interesting, especially if it can help users discover data, understand data sets, and interact with them more naturally. For governance and security, one of the strengths of Starburst Galaxy is that you can centralize access to data while still controlling what different users are allowed to see. Role-based access, fine-grained permissions, and data masking are important because giving people easier access to data should not mean giving everyone access to everything. I think that is even more important than any AI capabilities that are introduced. If you do introduce AI, I think it should respect exactly the same data permissions and governance rules as the user that is accessing the data.

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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

"It's a very good and reasonably priced solution."

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

"I would recommend SPSS to someone who has just started trying to run a lot of modeling, it's a good starting point."

"It works fine. I have not had any stability issues; it is always up."

"SPSS Modeler is a friendly interface for a beginner user."

"Quickness and ease of use with the guarantee of robust modeling techniques and trustworthy accuracy."

"It is a great product for running statistical analysis."

"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."

More IBM SPSS Modeler pros

"Starburst Galaxy has positively impacted my organization by allowing us to rethink the strategy for data and architect data differently; instead of having multiple data marts and siloed data marts, we have a unified vision, and that is how it is changing."

"The most fundamental feature is the query engine, which is much faster than any of the competitors; Starburst is able to finish most queries within 10 seconds, which is especially important for many non-technical employees."

"Starburst Galaxy is becoming a cornerstone of our data platform, empowering us to make smarter and faster decisions across the organization."

"I use Starburst as a cost-efficient hosted option for Trino for data integration and ad-hoc analysis across a broad range of data sources."

"The main positive impact Starburst Galaxy has made is making data more accessible for analytics and reporting."

"Starburst has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."

"I am now able to answer questions in a couple of minutes that would otherwise take hours or days of time for my data engineering teams."

"Starburst on Trino, combined with our SQL-native data transformation tool SQLMesh, has delivered anywhere from a two to five times improvement in compute performance across our transformation DAG."

More Starburst Galaxy pros

Cons

"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."

"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."

"Easier coding language that is more flexible with other platforms."

"It's very stable, although it is not as user friendly as it could be."

"We have run into a few problems doing some entity matching/analytics using this portion of the software."

"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint."

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

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

More IBM SPSS Modeler cons

"The most persistent issue is the cluster spin-up time."

"Cluster startup time is another pain point, typically 3 to 5 minutes, which is not the worst with proper planning but can be annoying for ad-hoc work."

"Cluster startup time can be slow, sometimes taking over a minute."

"As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options."

"Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose."

"I think there are areas of improvement with respect to AI adaptability, and also in general, the amount of connectors working with other tools are areas where it can be expanded."

"I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs."

"There is still room for improved usability and diagnostics, especially for users who are not platform specialists."

More Starburst Galaxy cons

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."

"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."

"$5,000 annually."

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

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

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

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

"It is a huge increase to time savings."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Outsourcing Company

Financial Services Firm

Government

Construction Company

Financial Services Firm

30%

Computer Software Company

10%

Manufacturing Company

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	4

Questions from the Community

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

What advice do you have for others considering IBM SPSS Modeler?

You should put MATLAB into your database. According to Gartner, from what I have seen last year, there was a Gartner four quadrants perspective, and MATLAB was in a very good position. I remember a...

See all answers

What is your experience regarding pricing and costs for Starburst Galaxy?

I recommend experimenting with different cluster sizes to determine what works best for your particular use case.

See all answers

What needs improvement with Starburst Galaxy?

See all answers

What is your primary use case for Starburst Galaxy?

I have mainly used Starburst Galaxy as a query and access layer for analytical data, as my current work involves dealing with data stored across different platforms, including Hive and SingleStore....

See all answers

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Compared 5% of the time

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Compared 19% of the time

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Compared 6% of the time

Qlik Talend Cloud vs Starburst Galaxy

Compared 5% of the time

IBM Watson Studio vs Starburst Galaxy

Compared 3% of the time

More Starburst Galaxy Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

October 2026

Download IBM SPSS Modeler product report

Buyer's Guide

Starburst Galaxy

September 2026

Download Starburst Galaxy product report

Also Known As

SPSS Modeler

No data available

Overview

IBM SPSS Modeler is a robust tool that facilitates predictive modeling and data analysis through intuitive visual programming and customizable automation, enabling users to streamline data analytics processes with effectiveness.

IBM SPSS Modeler combines ease of use with powerful functionalities, including statistical analysis and quick prototyping. Users can leverage visual programming and drag-and-drop features, making data exploration efficient. Its diverse algorithms and capability to handle large datasets enable comprehensive data cleansing and predictive modeling. Integrating smoothly with Python enhances its versatility. However, improvements in machine learning algorithms, platform compatibility, and visualization tools are necessary. Licensing costs and existing performance issues may require consideration, particularly concerning data extraction and interface convenience.

What are the critical features of IBM SPSS Modeler?

Ease of Use: Features intuitive visual programming, facilitating smooth operation.
Customizable Automation: Supports personalized automation processes.
Visual Programming: Employs drag-and-drop interfaces for efficient task execution.
Integration with Python: Enhances flexibility with Python compatibility.
Diverse Algorithms: Supports a wide range of algorithms for data analysis.
Data Cleansing and Modeling: Enables rigorous data cleansing and predictive modeling.

What benefits or ROI should users consider?

Enhanced Productivity: Streamlined processes improve efficiency.
Flexible Integration: Accommodates R and Python, boosting adaptability.
Scalable Analytics: Capably handles large datasets and complex models.
Quick Prototyping: Facilitates rapid model development.
Improved Insights: Delivers profound analytical insights for decision-making.

IBM SPSS Modeler is implemented across various industries for diverse applications, including data analytics, predictive modeling, and HR analytics. Organizations utilize it to build models for customer segmentation and predictive analysis, leveraging its capabilities for large datasets, research, and educational purposes. It integrates efficiently with cloud and on-premise solutions, enhancing business analytics applications.

IBM

Starburst Galaxy offers rapid query speeds and robust cluster management, enhancing data engineering efficiency while supporting AWS integrations and cross-database functionality. Users benefit from its advanced data integration and federated querying capabilities.

Starburst Galaxy stands out with a compute-focused architecture that excels in facilitating seamless data integration. Technological innovations like autoscaling clusters and automated metadata management optimize operations in multi-tenant environments. With a keen emphasis on compatibility, the platform provides support for AWS Glue and enables federated querying across S3, Snowflake, and Redshift. This adaptability ensures comprehensive ETL processes and enhances analytics through querying SQL Server, Google Sheets, and blob stores. While noted for its robust capabilities, users seek improvements in cluster startup times, Tableau and AI support, and desire infrastructure-as-code enhancements.

What are Starburst Galaxy's key features?

Rapid Query Speeds: Enhances data processing with quick responses.
Cluster Autoscaling: Optimizes resource allocation for varying workloads.
Federated Querying: Cross-database functionality for seamless integration.
Compute-Focused Architecture: Ensures efficiency and scalability.
Automated Metadata Management: Streamlines data handling processes.
AWS Integration: Broad compatibility with AWS services.

What benefits should users evaluate in reviews?

Data Engineering Efficiency: Reduces operating expenses and improves productivity.
Cost Reduction: Highlights lower storage costs with efficient data handling.
Seamless Integration: Enables robust data integration across various platforms.
Cluster Management: Supports diverse workloads with advanced management tools.

In industries focusing on large-scale data efforts, Starburst Galaxy plays an essential role in connecting data sources like Amazon S3 and RDS, streamlining tasks in data engineering and ad-hoc analysis across complex environments. Teams leverage its cross-database querying to boost AWS analytics, with features tailored for sectors needing agile data solutions, from ETL pipelines to secure data federation.

Starburst

Sample Customers

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

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Buyer's Guide

IBM SPSS Modeler vs. Starburst Galaxy

September 2026

Free Report: IBM SPSS Modeler vs. Starburst Galaxy

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