Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Rapidminer is a Siemens enterprise analytics and AI platform designed to help organizations connect fragmented data, build trusted models, and scale intelligent automation. It brings together data preparation, machine learning, knowledge graphs, generative AI, and AI agents in one portfolio. Businesses can use Rapidminer to break down data silos, unlock information trapped in documents, and add business context to analytics workflows. The platform supports users who want to modernize legacy systems while continuing to run existing SAS language programs. Rapidminer also includes visual tools for data science, allowing teams to design explainable machine learning models through drag-and-drop workflows. Its self-service data preparation features help users cleanse and transform data from PDFs, spreadsheets, databases, and cloud sources without coding. Real-time visualization and streaming analytics tools help organizations monitor fast-moving data and create interactive analytic applications. Rapidminer Graph Studio adds a semantic knowledge graph foundation that supports contextual reasoning and agentic AI. By combining automation, explainability, and enterprise-ready governance, Rapidminer helps companies turn data into stronger decisions and faster innovation.
Description
Easily create and modify database models through a user-friendly interface that simplifies the process. The forms clearly indicate which fields are mandatory for accurate SQL code generation. You are free to obtain, alter, and share the source code at no cost. This project features a public repository offering full access and the ability to fork the code, enabling developers to craft their own variations based on the original. Built on the Qt framework, pgModeler is compatible with Windows, Linux, and macOS, and its build scripts can be easily adjusted to address specific dependencies unique to each operating system. You can design a model once and export it across various versions effortlessly. With its dynamic code generation capabilities, pgModeler supports exporting to multiple PostgreSQL versions, ranging from 9.x to 13.x. If you find that certain features are lacking, you can utilize the plug-in development interface to create custom extensions for pgModeler without altering the core code. Moreover, this flexibility allows developers to enhance their database modeling experience and tailor it to their specific needs.
API Access
Has API
No
API Access
Has API
No
Integrations
Axon Ivy
Yes
Azure Marketplace
Yes
Datalytics
Yes
MeaningCloud
Yes
PostgreSQL
No
RapidProM
Yes
Rapidminer AI Studio
Yes
Rapidminer Knowledge Studio
Yes
Rapidminer Monarch
Yes
Rapidminer Panopticon
Yes
Integrations
Axon Ivy
No
Azure Marketplace
No
Datalytics
No
MeaningCloud
No
PostgreSQL
Yes
RapidProM
No
Rapidminer AI Studio
No
Rapidminer Knowledge Studio
No
Rapidminer Monarch
No
Rapidminer Panopticon
No
Pricing Details
Free
Free Trial
Yes
Free Version
Yes
Pricing Details
$49.90 one-time payment
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Siemens
Founded
1847
Country
Germany
Website
www.siemens.com/en-us/products/rapidminer/
Vendor Details
Company Name
pgModeler
Founded
2006
Country
Brazil
Website
pgmodeler.io
Product Features
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Mining
Data Extraction
No
Data Visualization
No
Fraud Detection
No
Linked Data Management
No
Machine Learning
No
Predictive Modeling
No
Semantic Search
No
Statistical Analysis
No
Text Mining
No
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No