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.
$4,670
per year
RapidMiner
Score 8.9 out of 10
N/A
RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.
$7,500
Per User Per Month
Pricing
IBM SPSS Modeler
RapidMiner
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
Professional
$7,500.00
Per User Per Month
Enterprise
$15,000.00
Per User Per Month
AI Hub
$54,000.00
Per User Per Month
Offerings
Pricing Offerings
IBM SPSS Modeler
RapidMiner
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
IBM 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.
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More Pricing Information
Community Pulse
IBM SPSS Modeler
RapidMiner
Features
IBM SPSS Modeler
RapidMiner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Modeler
7.0
Ratings
18% below category average
RapidMiner
9.5
Ratings
13% above category average
Connect to Multiple Data Sources
7.00 Ratings
10.00 Ratings
Extend Existing Data Sources
7.00 Ratings
10.00 Ratings
Automatic Data Format Detection
00 Ratings
9.00 Ratings
MDM Integration
00 Ratings
9.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM SPSS Modeler
-
Ratings
RapidMiner
9.0
Ratings
7% above category average
Visualization
00 Ratings
9.00 Ratings
Interactive Data Analysis
00 Ratings
9.00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM SPSS Modeler
-
Ratings
RapidMiner
8.8
Ratings
8% above category average
Interactive Data Cleaning and Enrichment
00 Ratings
9.00 Ratings
Data Transformations
00 Ratings
7.00 Ratings
Data Encryption
00 Ratings
9.00 Ratings
Built-in Processors
00 Ratings
10.00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM SPSS Modeler
-
Ratings
RapidMiner
9.0
Ratings
7% above category average
Multiple Model Development Languages and Tools
00 Ratings
9.00 Ratings
Automated Machine Learning
00 Ratings
9.00 Ratings
Single platform for multiple model development
00 Ratings
9.00 Ratings
Self-Service Model Delivery
00 Ratings
9.00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Modeler is well suited for understanding consumer data. The ability to create a prediction and then to understand what is driving that prediction is strong in Modeler. Modeler is closely aligned with the CRISP-DM data mining approach meaning it is not just the 'doing' but also the theoretical background behind the development of data mining models.
RapidMiner is the best tool to build models on textual data. It is rich in ML algorithms and reduces the need to manually tune the parameters. It automatically optimizes them, thus providing a better solution. RapidMiner again extends great capability for data preparation, its insane connections to almost every data source pulls in the data easily into one environment. And it can comfortably perform data cleaning and process tasks over that. RapidMiner is not so good with image, audio or video data. These data points cannot be used directly in their raw form. They must be transformed into some intermediate form for performing analytics over it. Moreover, there are no connectors to directly pull data from their varied sources. For example, we don't have a connector to read audio data directly from a switch and then convert it to text (although Google speech API is available for audio to text conversion.)
Wish the tool was more efficient in terms of processing power. The tool takes a lot of CPU processing power, even for a small process on a small data set
Wish there were more options on charts and graphs to visualize the data
The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and I really like several of the helpful components for usability for SPSS like peaks into nodes.
The other product like RapidMiner Studio that I have used is WEKA. I decided to use RapidMiner because almost all modelling methods and feature selection methods from the Weka machine learning library are available within RapidMiner. Furthermore, RapidMiner Studio is a visual workflow and therefore it is easier to demonstrate and visualise the processes involves in getting the desired results. Visualization of workflow enhances teaching and learning. RapidMiner is rich with algorithms and online learning materials that can assist students in their self-directed learning on data preparation, machine learning, deep learning, text mining, and predictive analytics. Moreover, RapidMiner repository has more than 1500 machine learning algorithms and functions that students can explore for any case study and assignments. The RapidMIner is also an open platform that can seamlessly integrates with other applications programmed with other programming languages like R and Python.