IBM ILOG CPLEX Optimization Studio vs. IBM SPSS Modeler

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM ILOG CPLEX Optimization Studio
Score 9.3 out of 10
N/A
IBM® ILOG® CPLEX® Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models using mathematical and constraint programming.
$199
Per User Per Month
IBM SPSS Modeler
Score 7.8 out of 10
N/A
IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.
$499
per month
Pricing
IBM ILOG CPLEX Optimization StudioIBM SPSS Modeler
Editions & Modules
Developer Subscription
$199.00
Per User Per Month
IBM SPSS Modeler Personal
4,670
per year
IBM SPSS Modeler Professional
7,000
per year
IBM SPSS Modeler Premium
11,600
per year
IBM SPSS Modeler Gold
contact IBM
per year
Offerings
Pricing Offerings
IBM ILOG CPLEX Optimization StudioIBM SPSS Modeler
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.
More Pricing Information
Community Pulse
IBM ILOG CPLEX Optimization StudioIBM SPSS Modeler
Top Pros

No answers on this topic

Top Cons
Features
IBM ILOG CPLEX Optimization StudioIBM SPSS Modeler
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM ILOG CPLEX Optimization Studio
8.0
2 Ratings
6% below category average
IBM SPSS Modeler
-
Ratings
Connect to Multiple Data Sources9.02 Ratings00 Ratings
Extend Existing Data Sources7.02 Ratings00 Ratings
Automatic Data Format Detection8.02 Ratings00 Ratings
MDM Integration8.02 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM ILOG CPLEX Optimization Studio
10.0
2 Ratings
17% above category average
IBM SPSS Modeler
-
Ratings
Visualization10.02 Ratings00 Ratings
Interactive Data Analysis10.02 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM ILOG CPLEX Optimization Studio
7.3
2 Ratings
12% below category average
IBM SPSS Modeler
-
Ratings
Interactive Data Cleaning and Enrichment5.01 Ratings00 Ratings
Data Transformations7.01 Ratings00 Ratings
Data Encryption8.02 Ratings00 Ratings
Built-in Processors9.02 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM ILOG CPLEX Optimization Studio
8.0
2 Ratings
6% below category average
IBM SPSS Modeler
-
Ratings
Multiple Model Development Languages and Tools10.02 Ratings00 Ratings
Automated Machine Learning5.01 Ratings00 Ratings
Single platform for multiple model development8.02 Ratings00 Ratings
Self-Service Model Delivery9.01 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
IBM ILOG CPLEX Optimization Studio
10.0
2 Ratings
15% above category average
IBM SPSS Modeler
-
Ratings
Flexible Model Publishing Options10.02 Ratings00 Ratings
Security, Governance, and Cost Controls10.02 Ratings00 Ratings
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Score 7.8 out of 10
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Score 8.2 out of 10
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Score 7.8 out of 10
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User Ratings
IBM ILOG CPLEX Optimization StudioIBM SPSS Modeler
Likelihood to Recommend
9.0
(2 ratings)
10.0
(6 ratings)
Usability
9.0
(1 ratings)
-
(0 ratings)
Support Rating
7.0
(1 ratings)
10.0
(1 ratings)
User Testimonials
IBM ILOG CPLEX Optimization StudioIBM SPSS Modeler
Likelihood to Recommend
IBM
It is well suited for solving large-sized, mixed-integer, and integer programming problems. Now, the new version supports for Multi-Objective optimization along with some new algorithms such as Benders Decomposition. It is less appropriate for quadratic programming problems where the objective function is the product of multiple variables. However, it's very easy to code any problem.
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IBM
Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
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Pros
IBM
  • Linear Programming
  • Mixed-Integer Linear Programming
  • Non-Linear Convex-Optimization
  • Visualization
  • Shadow Price Analysis
  • Parameter Tuning
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IBM
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
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Cons
IBM
  • Data handling from different sources like Note Pad, etc.
  • Large size of MILP problems.
  • Various parameters to set.
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IBM
  • Has very old style graphs, with lots of limitations.
  • Some advanced statistical functions cannot be done through the menu.
  • The data connectivity is not that extensive.
  • It's an expensive tool.
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Usability
IBM
It's nice to use and with good optimization.
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IBM
No answers on this topic
Support Rating
IBM
Honestly, to say, I never contacted CPLEX but used its forum to know/clarify any issues I faced.
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IBM
The online support board is helpful and the free add ons are incredibly appreciated.
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Alternatives Considered
IBM
IBM CPLEX Optimization Studio covers wide range of problems in comparison to Gurobi and also offers a number of visualization tools for results analysis. It has better customization and parameter tuning options in comparison to Gurobi. It offers various API integrations such as Python, Java and C++ which is not the case with Gurobi.
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IBM
When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
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Return on Investment
IBM
  • Faster computation leading to better internal customer relations
  • Able to solve high variable problems with ease
  • Anomaly detection became easier within business
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IBM
  • Positive - Ease of decision making and reduction in product life cycle time.
  • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
  • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
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ScreenShots

IBM SPSS Modeler Screenshots

Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.