IBM SPSS Modeler vs Starburst Galaxy comparison

IBM and Starburst are both solutions in the Data Science Platforms category. IBM is ranked #13 with an average rating of 8.0, while Starburst is ranked #6 with an average rating of 9.5. IBM holds a 3.1% 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

3,939 Views
3,033 Comparison Views

86% willing to recommend

Starburst Galaxy

Read 11 Starburst Galaxy reviews

1,809 Views
1,429 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: June 2026).

Buyer's Guide

IBM SPSS Modeler vs. Starburst Galaxy

June 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

6th

Average Rating

9.4

Reviews Sentiment

2.5

Number of Reviews

Ranking in other categories

Streaming Analytics (8th)

Mindshare comparison

As of July 2026, in the Data Science Platforms category, the mindshare of IBM SPSS Modeler is 3.1%, up from 2.5% 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	3.1%
Other	95.4%

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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Niketan Kumar

Advisory Solutions Architect at Dell Technologies

Unified data querying has accelerated petabyte-scale analytics and simplified dashboard delivery

Starburst Galaxy offers me several best features, which include very fast querying results, automatic indexing of data for long tables, a cost-based optimizer which reduces the time to query large tables, and an agentic feature that lets me talk to my data.I find myself relying most on querying from different databases as well as automatic indexing in my day-to-day work, as I am a data science architect who needs to get the queries in a very short period of time. Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best. Starburst Galaxy has positively impacted my organization since we were struggling with Denodo and Dremio, which had their own features but were not helpful in querying large amounts of data, especially semi-structured or unstructured data. Starburst Galaxy addresses this with many YAML files and manifest files for automated maintenance, and it helps reduce the small file problem in different HDFS systems. Additionally, Starburst Galaxy has an MCP server that connects to various agentic pipelines, reducing the time to market for data consumption.

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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

"IBM SPSS Modeler is the easiest solution."

"Stability is good."

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

"It scales. I have not run into any challenges where it will not perform."

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

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

"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use."

"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

"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 Galaxy has significantly improved our data architecture flexibility and performance management by solving cross-database query challenges and enabling us to utilize iceberg tables externally across our entire data ecosystem."

"Starburst Galaxy serves as our primary SQL-based data processing engine, a strategic decision driven by its seamless integration with our AWS cloud infrastructure and its ability to deliver high performance with low-latency responses."

"Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best."

"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."

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

"Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."

More Starburst Galaxy pros

Cons

"Unstructured data is not appropriate for SPSS Modeler."

"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 platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

"Initial setup of the software was complex, because of our own problems within the government."

"Customer support is hard to contact."

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

More IBM SPSS Modeler cons

"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."

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

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

"Multi-tenancy could be improved. In order to have multiple environments for SSO, we maintain multiple tenants that are connected to different AWS accounts via the Marketplace."

"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."

"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."

"I would like Starburst to leverage AI to improve usability. Data lakes are complicated and difficult for users to explore."

More Starburst Galaxy cons

Pricing and Cost Advice

"$5,000 annually."

"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."

"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."

"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 is a huge increase to time savings."

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

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

"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

11%

Government

Construction Company

University

Financial Services Firm

29%

Computer Software Company

12%

Construction Company

University

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	3

Questions from the Community

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...

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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?

Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose. We rely on third-party tools for ingesti...

See all answers

What is your primary use case for Starburst Galaxy?

My main use case for Starburst Galaxy is querying petabytes of data across vast data sources, and I use a federated query engine to join data sources from different databases and then join them usi...

See all answers

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Compared 22% of the time

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Compared 10% of the time

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Dremio vs Starburst Galaxy

Compared 6% of the time

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Compared 3% of the time

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Product Reports

Buyer's Guide

IBM SPSS Modeler

June 2026

Download IBM SPSS Modeler product report

Buyer's Guide

Starburst Galaxy

June 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

Information Not Available

Buyer's Guide

IBM SPSS Modeler vs. Starburst Galaxy

June 2026

Free Report: IBM SPSS Modeler vs. Starburst Galaxy

Find out what your peers are saying about IBM SPSS Modeler vs. Starburst Galaxy and other solutions. Updated: June 2026.

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