IBM SPSS Modeler vs Starburst Enterprise comparison

IBM and Starburst are both solutions in the Data Science Platforms category. IBM is ranked #13 with an average rating of 6.8, while Starburst is ranked #14 with an average rating of 8.5. IBM holds a 2.4% mindshare in Data Science Platforms, compared to Starburst’s 2.2% 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 39 IBM SPSS Modeler reviews

1,793 Views
1,459 Comparison Views

86% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,176 Views
1,011 Comparison Views

100% willing to recommend

IBM SPSS Modeler

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and Starburst Enterprise are both data solutions in the data processing and analytics domain. Starburst Enterprise appears to have a competitive edge due to its ability to manage large data volumes with speed and scalability, which is advantageous for enterprises with extensive data sets.

Features: IBM SPSS Modeler is renowned for its advanced statistical analysis tools, intuitive interface, and predictive analytics capabilities that simplify complex data analysis. Starburst Enterprise excels with its Presto-based architecture that efficiently queries and processes large-scale data across various sources without requiring data movement. The differentiation is clear: SPSS Modeler targets statistical and predictive tasks, whereas Starburst Enterprise is designed for big data querying and integration.

Ease of Deployment and Customer Service: IBM SPSS Modeler provides an easy setup process that integrates well with existing data systems, offering robust technical support for organizations needing detailed predictive analytics. Starburst Enterprise, while having a more extensive deployment due to its distributed architecture, compensates with high scalability and performance, supported by excellent service for enterprises requiring fast data processing solutions. This underscores the trade-off between deployment complexity and scalability.

Pricing and ROI: IBM SPSS Modeler generally has a higher upfront cost but delivers significant ROI for organizations focused on in-depth statistical analysis and predictive modeling. Starburst Enterprise offers flexible pricing for large-scale operations, often providing high ROI through effective querying capabilities and cost-effective scalability. This highlights IBM SPSS Modeler's strength in predictive analytics against Starburst Enterprise's efficiency in scalable data processing.

To learn more, read our detailed IBM SPSS Modeler vs. Starburst Enterprise Report (Updated: April 2025).

Buyer's Guide

IBM SPSS Modeler vs. Starburst Enterprise

April 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

IBM SPSS Modeler

Ranking in Data Science Platforms

13th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Mining (4th)

Starburst Enterprise

Ranking in Data Science Platforms

14th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Streaming Analytics (12th)

Mindshare comparison

As of May 2025, in the Data Science Platforms category, the mindshare of IBM SPSS Modeler is 2.4%, down from 2.7% compared to the previous year. The mindshare of Starburst Enterprise is 2.2%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

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.

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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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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

"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."

"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."

"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more. For example, segmentation projects now take one to three months, rather than six months to a year, as before."

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

"We have been able to do some predictive modeling with it"

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

"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"

"It is pretty scalable."

More IBM SPSS Modeler pros

"It's very scalable, fast performing, and supports many catalogs."

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

Cons

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

"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."

"Unstructured data is not appropriate for SPSS Modeler."

"The platform's cloud version needs improvements."

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

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

"I think mapping for geographic data would also be a really great thing to be able to use."

"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."

More IBM SPSS Modeler cons

"There should be support for REST API data sources to access data from the web."

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

Pricing and Cost Advice

"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."

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

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

"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."

"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."

"$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."

More IBM SPSS Modeler pricing and cost advice

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Educational Organization

11%

University

Computer Software Company

Financial Services Firm

45%

Computer Software Company

Energy/Utilities Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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

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

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

See all answers

What needs improvement with Starburst Enterprise?

See all answers

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

See all answers

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Compared 9% of the time

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Product Reports

Buyer's Guide

IBM SPSS Modeler

April 2025

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Buyer's Guide

Data Science Platforms

March 2025

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Also Known As

SPSS Modeler

No data available

Overview

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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IBM

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

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 Enterprise

April 2025

Free Report: IBM SPSS Modeler vs. Starburst Enterprise

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