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IBM SPSS Modeler vs IBM Smart Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

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 Smart Analytics
Ranking in Data Mining
10th
Average Rating
7.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
IBM SPSS Modeler
Ranking in Data Mining
4th
Average Rating
8.0
Reviews Sentiment
6.6
Number of Reviews
39
Ranking in other categories
Data Science Platforms (14th)
 

Mindshare comparison

As of July 2025, in the Data Mining category, the mindshare of IBM Smart Analytics is 1.0%, up from 0.6% compared to the previous year. The mindshare of IBM SPSS Modeler is 17.9%, up from 16.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Mining
 

Featured Reviews

RH
Adding LA on top of a well deployed & working Tivoli Framework opens up a flood of native logged data points. The visual presentation layer of LA is less than cutting edge.
The IBM monitoring software products (Tivoli) are not easy to instrument and require many separate pieces of the total framework to be operationally functional and useable. That said, adding LA on top of a well deployed & working Tivoli Framework opens up a flood of native logged data points for unstructured search & query. My team had a special need to implement custom alerting on 10s of thousands of MQ channels in a short amount of time, and the traditional approach (also w a Tivoli product) would have been very costly (labor) and time consuming (requiring individual app review). As an alternative, we had a new event stream create to track all MQ channels to generate logs and then used LA to visualize the behavior trends for review, reporting and eventually alerting. The effort took longer than I hoped ~6 months, but the traditional approach would have taken 2+ yrs to review and implement app by app.
PeterHuo - PeerSpot reviewer
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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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
12%
Educational Organization
10%
Government
9%
University
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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What do you like most about IBM SPSS Modeler?
Compared to other tools, the product works much easier to analyze data without coding.
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...
What needs improvement with IBM 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 performanc...
 

Comparisons

No data available
 

Also Known As

Smart Analytics
SPSS Modeler
 

Overview

 

Sample Customers

WIdO AOK, EEKA Fashion, SSGC, GS Retail
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
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: June 2025.
859,579 professionals have used our research since 2012.