Top Alternatives to Scilab

Looking for Scilab alternatives? We've curated 9 top alternatives that offer similar functionality. Whether you need options, free plans, or open source solutions, explore our comprehensive list to find the perfect fit for your needs.

Open Source More about Scilab

Categories:

Education & Reference

Platforms:

MATLAB

Commercial

MATLAB is a comprehensive platform for numerical computing, visualization, and programming. It provides a powerful environment for algorithm development, data analysis, simulation, and model development across various disciplines.

Key Features

Comprehensive numerical computing environment.
Extensive collection of domain-specific toolboxes.
Powerful visualization capabilities.

vs Scilab

Comprehensive numerical computing environment. compared to Scilab

GNU Octave

Open Source

GNU Octave is a high-level programming language primarily intended for numerical computations. It provides a convenient command-line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments.

Key Features

Free and open-source, accessible to everyone.
High compatibility with MATLAB syntax and functions.
Extensive library of built-in numerical functions.

vs Scilab

Free and open-source, accessible to everyone. compared to Scilab

R (programming language)

Open Source

R is a powerful open-source language and environment for statistical computing, graphics, and data analysis. Widely used by statisticians and data miners for developing statistical software and data analysis.

Key Features

Extensive statistical and graphical capabilities.
Large and comprehensive ecosystem of packages.
High-quality data visualization features.

vs Scilab

Extensive statistical and graphical capabilities. compared to Scilab

Sage

Open Source

SageMath is a free open-source mathematics software system that provides a comprehensive environment for symbolic and numerical computation, algebra, calculus, and more. It integrates various existing mathematics software packages into a common Python-based interface.

Key Features

Free and open-source
Comprehensive range of mathematical capabilities
Excellent interactive notebook interface

vs Scilab

Free and open-source compared to Scilab

SciPy & Numpy

Open Source

NumPy and SciPy form a foundational ecosystem in Python for numerical and scientific computing, providing powerful tools for mathematical operations, linear algebra, statistics, and optimization.

Key Features

Excellent performance for numerical computations.
Comprehensive set of mathematical and scientific functions.
Forms the foundation for many other Python libraries.

vs Scilab

Excellent performance for numerical computations. compared to Scilab

python(x,y)

Open Source

Python(x,y) is a comprehensive, free and open-source development environment for scientific and engineering tasks using Python. It bundles numerous libraries and tools for numerical computation, data analysis, visualization, and more, making it a powerful alternative to commercial software.

Key Features

Bundled with essential scientific libraries.
Easy to install and set up.
Includes a comprehensive IDE with debugger.

vs Scilab

Bundled with essential scientific libraries. compared to Scilab

Spyder

Open Source

Spyder is a comprehensive Scientific Python Development Environment (IDE) designed specifically for data scientists, engineers, and researchers using Python for scientific computing. It offers a rich set of tools for interactive data exploration, analysis, and visualization.

Key Features

Excellent integration with the scientific Python ecosystem (NumPy, SciPy, Pandas, Matplotlib).
Variable Explorer is highly effective for data inspection and manipulation.
Integrated IPython console allows for interactive code execution and exploration.

vs Scilab

Excellent integration with the scientific Python ecosystem (NumPy, SciPy, Pandas, Matplotlib). compared to Scilab

fxSolver

Free

fxSolver is a powerful online tool designed for solving complex mathematical, scientific, and engineering equations with ease. It features a vast library of formulas and a user-friendly interface, allowing users to input, solve, and visualize equations and data.

Key Features

Extensive database of pre-built formulas saves significant time.
User-friendly online interface accessible from any device.
Integrated graphing and plotting for visual analysis.

vs Scilab

Extensive database of pre-built formulas saves significant time. compared to Scilab

Freemat

Open Source

FreeMat is a free and open-source environment designed for engineering and scientific prototyping, data analysis, and numeric computation. It provides a MATLAB-like environment for users working with mathematical and scientific data, focusing on ease of use and powerful analytical capabilities.

Key Features

Free and open-source alternative to commercial software.
Familiar syntax for users of MATLAB-like environments.
Comprehensive library of mathematical functions.

vs Scilab

Free and open-source alternative to commercial software. compared to Scilab

MATLAB

Commercial

MATLAB is a comprehensive platform for numerical computing, visualization, and programming. It provides a powerful environment for algorithm development, data analysis, simulation, and model development across various disciplines.

Key Features

Comprehensive numerical computing environment.
Extensive collection of domain-specific toolboxes.
Powerful visualization capabilities.

vs Scilab

Comprehensive numerical computing environment. compared to Scilab

GNU Octave

Open Source

GNU Octave is a high-level programming language primarily intended for numerical computations. It provides a convenient command-line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments.

Key Features

Free and open-source, accessible to everyone.
High compatibility with MATLAB syntax and functions.
Extensive library of built-in numerical functions.

vs Scilab

Free and open-source, accessible to everyone. compared to Scilab

R (programming language)

Open Source

R is a powerful open-source language and environment for statistical computing, graphics, and data analysis. Widely used by statisticians and data miners for developing statistical software and data analysis.

Key Features

Extensive statistical and graphical capabilities.
Large and comprehensive ecosystem of packages.
High-quality data visualization features.

vs Scilab

Extensive statistical and graphical capabilities. compared to Scilab

Sage

Open Source

SageMath is a free open-source mathematics software system that provides a comprehensive environment for symbolic and numerical computation, algebra, calculus, and more. It integrates various existing mathematics software packages into a common Python-based interface.

Key Features

Free and open-source
Comprehensive range of mathematical capabilities
Excellent interactive notebook interface

vs Scilab

Free and open-source compared to Scilab

SciPy & Numpy

Open Source

NumPy and SciPy form a foundational ecosystem in Python for numerical and scientific computing, providing powerful tools for mathematical operations, linear algebra, statistics, and optimization.

Key Features

Excellent performance for numerical computations.
Comprehensive set of mathematical and scientific functions.
Forms the foundation for many other Python libraries.

vs Scilab

Excellent performance for numerical computations. compared to Scilab

python(x,y)

Open Source

Python(x,y) is a comprehensive, free and open-source development environment for scientific and engineering tasks using Python. It bundles numerous libraries and tools for numerical computation, data analysis, visualization, and more, making it a powerful alternative to commercial software.

Key Features

Bundled with essential scientific libraries.
Easy to install and set up.
Includes a comprehensive IDE with debugger.

vs Scilab

Bundled with essential scientific libraries. compared to Scilab

Spyder

Open Source

Spyder is a comprehensive Scientific Python Development Environment (IDE) designed specifically for data scientists, engineers, and researchers using Python for scientific computing. It offers a rich set of tools for interactive data exploration, analysis, and visualization.

Key Features

Excellent integration with the scientific Python ecosystem (NumPy, SciPy, Pandas, Matplotlib).
Variable Explorer is highly effective for data inspection and manipulation.
Integrated IPython console allows for interactive code execution and exploration.

vs Scilab

Excellent integration with the scientific Python ecosystem (NumPy, SciPy, Pandas, Matplotlib). compared to Scilab

fxSolver

Free

fxSolver is a powerful online tool designed for solving complex mathematical, scientific, and engineering equations with ease. It features a vast library of formulas and a user-friendly interface, allowing users to input, solve, and visualize equations and data.

Key Features

Extensive database of pre-built formulas saves significant time.
User-friendly online interface accessible from any device.
Integrated graphing and plotting for visual analysis.

vs Scilab

Extensive database of pre-built formulas saves significant time. compared to Scilab

Freemat

Open Source

FreeMat is a free and open-source environment designed for engineering and scientific prototyping, data analysis, and numeric computation. It provides a MATLAB-like environment for users working with mathematical and scientific data, focusing on ease of use and powerful analytical capabilities.

Key Features

Free and open-source alternative to commercial software.
Familiar syntax for users of MATLAB-like environments.
Comprehensive library of mathematical functions.

vs Scilab

Free and open-source alternative to commercial software. compared to Scilab

Compare Side-by-Side

Want to see how Scilab stacks up against alternatives? Select any option below for a detailed comparison.

MATLAB vs Scilab

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GNU Octave icon

GNU Octave vs Scilab

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R (programming language) icon

R (programming language) vs Scilab

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SciPy & Numpy icon

SciPy & Numpy vs Scilab

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python(x,y) icon

python(x,y) vs Scilab

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Spyder vs Scilab

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fxSolver vs Scilab

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Freemat vs Scilab

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