MATLAB vs. RT-LAB vs. scikit-learn Comparison


MATLAB The MathWorks	RT-LAB OPAL-RT TECHNOLOGIES	scikit-learn	+
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About MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design.	About RT-LAB is OPAL-RT’s real-time simulation software combining performance and enhanced user experience. Fully integrated with MATLAB/Simulink®, RT-LAB offers the most complex model-based design for interaction with real-world environments. It provides the flexibility and scalability to achieve the most complex real-time simulation applications in the automotive, aerospace, power electronics, and power systems industries. Since its first application nearly 20 years ago on the Canadian Space Agency’s Canada Arm, RT-LAB has revolutionized the world of systems engineering, whether in space, on the ground or at sea. RT-LAB enables engineers and scientists to accelerate the development of new prototypes and to meet the most rigorous testing required by new and innovative technologies. RT-LAB handles everything, including code generation, with an easy-to-use interface. With just a few clicks of the mouse, a Simulink® model becomes an interactive real-time simulation application.	About Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.
Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook	Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook	Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook
Audience Modeling, simulation, and programming software that can be hosted in the cloud or on-premise	Audience Automotive companies in need of a real-time simulation solution	Audience Engineers and data scientists requiring a solution to manage and improve their machine learning research
Support Phone Support 24/7 Live Support Online	Support Phone Support 24/7 Live Support Online	Support Phone Support 24/7 Live Support Online
API Offers API	API Offers API	API Offers API
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Pricing No information available. Free Version Free Trial	Pricing No information available. Free Version Free Trial	Pricing Free Free Version Free Trial
Reviews/Ratings Overall 4.7 / 5 ease 4.5 / 5 features 4.9 / 5 design 4.8 / 5 support 4.8 / 5 Read all reviews	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software
Training Documentation Webinars Live Online In Person	Training Documentation Webinars Live Online In Person	Training Documentation Webinars Live Online In Person
Company Information The MathWorks Founded: 1984 United States www.mathworks.com	Company Information OPAL-RT TECHNOLOGIES Founded: 1997 Canada www.opal-rt.com/software-rt-lab/	Company Information scikit-learn United States scikit-learn.org/stable/
Alternatives Posit	Alternatives Simulink MathWorks	Alternatives Gensim Radim Řehůřek
PrimeSim HSPICE Synopsys	MATLAB The MathWorks	ML.NET Microsoft
LabVIEW NI	System Composer MathWorks	MLlib Apache Software Foundation
LiveLink for MATLAB Comsol Group	UberCloud Simr (formerly UberCloud)	Dask
RunMat Dystr View All	YAKINDU Model Viewer itemis AG View All	Keepsake Replicate View All
Categories Backtesting CAD Computer-Aided Engineering (CAE) Data Science Data Visualization Embedded Software Development Engineering Financial Risk Management Fraud Detection Mechanical Engineering Predictive Analytics Programming Languages Simulation Statistical Analysis	Categories Simulation	Categories Machine Learning
Show More Features CAD Features 2 1/2-Axis Milling 2D Drawing 3-Axis Milling 3D Modeling 4-Axis Milling 5-Axis Milling Civil Collaboration Database Connectivity Design Analysis Design Export Document Management Electrical Hole Making Mechanical Mechatronics Presentation Tools Simulate Cycles Spiral Output Structural Engineering Toolpath Simulation User Defined Cycles Engineering Features 2D Drawing 3D Modeling Chemical Engineering Civil Engineering Collaboration Design Analysis Design Export Document Management Electrical Engineering Mechanical Engineering Mechatronics Presentation Tools Structural Engineering Financial Risk Management Features Compliance Management Credit Risk Management For Hedge Funds Liquidity Analysis Loan Portfolio Management Market Risk Management Operational Risk Management Portfolio Management Portfolio Modeling Risk Analytics Benchmarks Stress Tests Value At Risk Calculation Simulation Features 1D Simulation 3D Modeling 3D Simulation Agent-Based Modeling Continuous Modeling Design Analysis Direct Manipulation Discrete Event Modeling Dynamic Modeling Graphical Modeling Industry Specific Database Monte Carlo Simulation Motion Modeling Presentation Tools Stochastic Modeling Turbulence Modeling Statistical Analysis Features Analytics Association Discovery Compliance Tracking File Management File Storage Forecasting Multivariate Analysis Regression Analysis Statistical Process Control Statistical Simulation Survival Analysis Time Series Visualization
Integrations Azure Marketplace Candera CGI Studio Codebeamer Databricks Data Intelligence Platform Domino Enterprise MLOps Platform Gemini Code Assist Matplotlib OnScale Solve OpenCV OpenCage Geocoding API OptiTrack Motive Overleaf PACE Anti-Piracy Pop!_OS Python Simcenter Flotherm Snipplr ThingSpeak VIKTOR Wing Python IDE Show More Integrations View All 77 Integrations	Integrations Azure Marketplace Candera CGI Studio Codebeamer Databricks Data Intelligence Platform Domino Enterprise MLOps Platform Gemini Code Assist Matplotlib OnScale Solve OpenCV OpenCage Geocoding API OptiTrack Motive Overleaf PACE Anti-Piracy Pop!_OS Python Simcenter Flotherm Snipplr ThingSpeak VIKTOR Wing Python IDE Show More Integrations	Integrations Azure Marketplace Candera CGI Studio Codebeamer Databricks Data Intelligence Platform Domino Enterprise MLOps Platform Gemini Code Assist Matplotlib OnScale Solve OpenCV OpenCage Geocoding API OptiTrack Motive Overleaf PACE Anti-Piracy Pop!_OS Python Simcenter Flotherm Snipplr ThingSpeak VIKTOR Wing Python IDE Show More Integrations View All 12 Integrations
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