IBM SPSS Modeler vs Microsoft Power BI comparison

The compared IBM and Microsoft solutions aren't in the same category. IBM is ranked #4 in DM , with an average rating of 7.0, and holds a 17.9% mindshare in the category. Microsoft is ranked #1 in BIT , with an average rating of 7.8, and holds a 20.7% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 93% of Microsoft users who would recommend it.

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

2,280 Views
935 Comparison Views

86% willing to recommend

Microsoft Power BI

Read 321 Microsoft Power BI reviews

26,806 Views
16,352 Comparison Views

93% willing to recommend

IBM SPSS Modeler

Microsoft Power BI

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between IBM SPSS Modeler and Microsoft Power BI based on real PeerSpot user reviews.

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.

To learn more, read our detailed Data Mining Report (Updated: July 2025).

Buyer's Guide

Data Mining

July 2025

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Helped 864,053 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

IBM SPSS Modeler

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Mining (4th), Data Science Platforms (17th)

Microsoft Power BI

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

321

Ranking in other categories

BI (Business Intelligence) Tools (1st), Reporting (1st)

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. IBM SPSS Modeler is designed for Data Mining and holds a mindshare of 17.9%, up 16.3% compared to last year.
Microsoft Power BI, on the other hand, focuses on BI (Business Intelligence) Tools, holds 20.7% mindshare, down 21.9% since last year.

Data Mining

BI (Business Intelligence) Tools

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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Shoury Priyanshu

Senior Manager, Strategy & Consulting at Viacom18 Media Pvt Ltd

Facilitates seamless data aggregation with some outdated visual elements hindering user appeal

Real-time data integration is an area for improvement. Although I've worked on several solutions involving real-time integration, it's not very user-friendly and often lags, especially with over a million data rows. This makes Power BI difficult to manage as loading times can reach one or two minutes, which is problematic today. There are challenges with scalability, requiring multiple pages in dashboards to manage these issues. Visualization could be improved as it appears outdated. Users, especially newcomers, find it unappealing and not user-friendly.

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

"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."

"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."

"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."

"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."

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

"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."

"I was familiar with using IBM SPSS Modeler separately in the private sector before that. It's a good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data."

More IBM SPSS Modeler pros

"The ease of integration and connectivity stands out as the most critical aspect, followed closely by the flexibility to customize reports and dashboards."

"There is continual improvement year-over-year."

"The initial setup is relatively simple."

"The dashboard is very nice and it is very simple to understand every single component."

"The user experience is easy. Users get familiar with it quickly."

"We've used Microsoft BI for the general use cases around reporting and dashboarding."

"Power BI stands out because it provides considerable flexibility in creating reports, dashboards, and various types of analytics to meet those dynamic requirements. It is lightweight and easy to use with good support."

"The initial setup is easy."

More Microsoft Power BI pros

Cons

"The forecasting could be a bit easier."

"It would be beneficial if the tool would include more well-known machine learning algorithms."

"The platform's cloud version needs improvements."

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

"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."

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

"Unstructured data is not appropriate for SPSS Modeler."

"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."

More IBM SPSS Modeler cons

"The integration with other solutions could be improved for reporting aspects."

"I found data cleaning in the solution to be quite difficult. If I could add a feature, I'd include Excel's Flash Fill function. This allows you to set a formula for one row and column and automatically apply it to thousands of rows, making data sorting much easier."

"We face multiple issues, and the connection drops off multiple times while integrating Microsoft Power BI with OAC and pulling in the data."

"In Microsoft Excel, you are able to have tabs. However, in Microsoft BI you do not have this flexibility."

"Microsoft is behind IBM when it comes to security features."

"The solution is somewhat costly in comparison with MSBI tools."

"It is not yet ready for enterprises. For a big enterprise data model, it is not so stable, and it also doesn't scale so well."

"If you are having millions of rows of data or you have a large database, Microsoft BI's performance depends upon how powerful your hardware is. When I am handling large amounts of data I do not use Microsoft BI or Tableau because of this, I use D3."

More Microsoft Power BI cons

Pricing and Cost Advice

"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."

"It is an expensive product."

"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."

"$5,000 annually."

More IBM SPSS Modeler pricing and cost advice

"Pricing, that's where Microsoft beats Tableau. It is priced much cheaper."

"From a cost point of view, it's competitive in the enterprise space, although it's not as competitive when you add up all of the additional costs. Things like integrations cost extra and it's probably where Microsoft makes more of the money."

"MS BI comes with all the tools and it is, to the best of my knowledge, the most affordable solution."

"Setup is easy, and the cost is economical. You do sometimes need to pay additional costs for third party products which "plug-in" to Microsoft BI."

"Licensing is on a monthly basis, but I am not sure."

"Microsoft BI is not very cheap. A premium license costs roughly 5,000 euros a month."

"The premium capacity is very costly in respect of the market in Egypt, amounting to $5,000 monthly."

"It would be better if the price was cheaper."

More Microsoft Power BI pricing and cost advice

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Comparison Review

it_user79932

Senior Manager - BI Head at NVidia

Feb 4, 2015

Comparison of SAP BO, Tableau, QlikView, Cognos, Microsoft, OBIEE and Pentaho

1. SAP BO/BI Enterprise scalability Security Ease of use Semantic layer 2. Tableau Visualization Data discovery Turnaround time 3. IBM Cognos Enterprise scalability Security In-memory feature 4. MS BI - Flexibility 5. Pentaho - Open source but still enterprise grade 6. QlikView Data…

Read full review

Top Industries

By visitors reading reviews

Financial Services Firm

11%

Educational Organization

11%

Government

10%

University

Financial Services Firm

12%

Computer Software Company

Government

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

Seeking lightweight open source BI software

There are many...It would rather depend what System BI architecture or Enterprise legacy you have at your end...I would recommend as follows: 1) If you have legacies of SAP, Oracle - look for SAP...

See all answers

Is Power BI a complete platform or only a visualization tool?

Power BI is an advanced visualization tool oriented to big data with a very complete set of widgets to visualize information, control users accessing information, the configuration of governance po...

See all answers

How does Oracle OBIEE compare with Microsoft BI?

Oracle OBIEE is great in allowing design and creativity per the individual needs of the organization. Dashboards are fully customizable and very user-friendly. This solution is very stable. Oracle ...

See all answers

Comparisons

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Compared 22% of the time

KNIME Business Hub vs IBM SPSS Modeler

Compared 15% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

Alteryx vs IBM SPSS Modeler

Compared 6% of the time

Weka vs IBM SPSS Modeler

Compared 4% of the time

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Tableau vs Microsoft Power BI

Compared 13% of the time

Domo vs Microsoft Power BI

Compared 8% of the time

Amazon QuickSight vs Microsoft Power BI

Compared 8% of the time

Databricks vs Microsoft Power BI

Compared 7% of the time

SAP Analytics Cloud vs Microsoft Power BI

Compared 2% of the time

More Microsoft Power BI Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

July 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Microsoft Power BI

July 2025

Download Microsoft Power BI product report

Also Known As

SPSS Modeler

SSRS, SSAS, MSBI, MS Reporting Services, Microsoft BI Tools, Microsoft Big Data, Power BI Pro, MS BI

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

Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

Microsoft Power BI is a powerful tool for data analysis and visualization. This tool stands out for its ability to merge and analyze data from various sources. Widely adopted across different industries and departments, Power BI is instrumental in creating visually appealing dashboards and generating insightful business intelligence reports. Its intuitive interface, robust visualization capabilities, and seamless integration with other Microsoft applications empower users to easily create interactive reports and gain valuable insights.

Microsoft

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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Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: July 2025.

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