IBM SPSS Modeler vs. Oracle Machine Learning

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
Oracle Machine Learning
Score 8.0 out of 10
N/A
Oracle Machine Learning (formerly Oracle Advanced Analytics) combines the Oracle database with Oracle Data Miner and SQL as well as R programming language functionality, providing a complete predictive analytics suite.N/A
Pricing
IBM SPSS ModelerOracle Machine Learning
Editions & Modules
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
No answers on this topic
Offerings
Pricing Offerings
IBM SPSS ModelerOracle Machine Learning
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
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
Best Alternatives
IBM SPSS ModelerOracle Machine Learning
Small Businesses
Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.2 out of 10
Posit
Posit
Score 9.1 out of 10
Enterprises
Alteryx
Alteryx
Score 9.0 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerOracle Machine Learning
Likelihood to Recommend
10.0
(6 ratings)
8.0
(10 ratings)
Support Rating
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
IBM SPSS ModelerOracle Machine Learning
Likelihood to Recommend
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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Oracle
OAC doesn't require software to be installed since it is browser based. This allows for easier deployment since a local client software is not required to be installed for each user. OAC can be used for the casual light user who mainly consumes data to the power user who can created sophisticated dashboard with advanced analytics. OAC is not meant to replace Essbase reporting.
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Pros
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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Oracle
  • Analyzing heaps of data dumped into the machine learning tool.
  • Giving the researcher an insight on which direction to proceed in order to get the desired results.
  • Can help perform a functional analysis before doing a deep dive.
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Cons
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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Oracle
  • As mentioned by others the formatting of reports constantly has issues
  • Once your initial contract terms are up be prepared for a significant increase
  • Pricing needs to be inline with what other competitors are offering
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Support Rating
IBM
The online support board is helpful and the free add ons are incredibly appreciated.
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Oracle
No answers on this topic
Alternatives Considered
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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Oracle
Sorry this product was not selected by me, but was a legacy install that was upgraded. I see the value in the product, however, I was not involved in the selection process.
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Return on Investment
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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Oracle
  • Our ROI has been great since we have been able to get a birdseye view of our business operations.
  • Shows your areas within your company that needs attention and improvements.
  • Oracle has had a positive impact on all of our business objectives since it provides a clear view of your business operations.
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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.