Maxima vs Mathematica

Struggling to choose between Maxima and Mathematica? Both products offer unique advantages, making it a tough decision.

Maxima is a Education & Reference solution with tags like algebra, calculus, equations, matrices, stem.

It boasts features such as Symbolic manipulation of mathematical expressions, Numerical computations, 2D/3D plotting and visualization, Solving equations and systems of equations, Matrix operations, Integration and differentiation, Taylor series expansions, Laplace and Fourier transforms, Probability and statistics functions, Unit conversions and pros including Free and open source, Cross-platform compatibility, Extensive mathematical capabilities, Can be extended with new functions and features, Good documentation and active user community.

On the other hand, Mathematica is a Education & Reference product tagged with mathematics, symbolic-computation, data-visualization.

Its standout features include Symbolic and numerical computation, 2D and 3D data visualization, Programming language and development environment, Large library of mathematical, statistical, and machine learning functions, Natural language processing capabilities, Can be used for applications like data analysis, modeling, education, research, engineering, finance, and more., and it shines with pros like Very powerful and versatile for technical computing, Intuitive syntax and workflows, Excellent graphics, plotting, and visualization capabilities, Can handle both symbolic and numeric computations, Has many built-in algorithms, models, and datasets, Can automate complex tasks and workflows, Integrates well with other systems and languages.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Maxima

Maxima

Maxima is an open-source computer algebra system that provides symbolic computation capabilities. It can manipulate mathematical expressions, differentiate and integrate functions, solve equations, work with matrices, graphs, and more. Useful for STEM fields like math, engineering, physics.

Categories:
algebra calculus equations matrices stem

Maxima Features

  1. Symbolic manipulation of mathematical expressions
  2. Numerical computations
  3. 2D/3D plotting and visualization
  4. Solving equations and systems of equations
  5. Matrix operations
  6. Integration and differentiation
  7. Taylor series expansions
  8. Laplace and Fourier transforms
  9. Probability and statistics functions
  10. Unit conversions

Pricing

  • Open Source

Pros

Free and open source

Cross-platform compatibility

Extensive mathematical capabilities

Can be extended with new functions and features

Good documentation and active user community

Cons

Steep learning curve

User interface not very intuitive

Limited capabilities for numeric computations compared to MATLAB or NumPy

Graphics and visualization not as advanced as MATLAB or Mathematica


Mathematica

Mathematica

Mathematica is a computational software program used for symbolic mathematics, numerical calculations, data visualization, and more. It has a wide range of applications in STEM fields including physics, chemistry, biology, and finance.

Categories:
mathematics symbolic-computation data-visualization

Mathematica Features

  1. Symbolic and numerical computation
  2. 2D and 3D data visualization
  3. Programming language and development environment
  4. Large library of mathematical, statistical, and machine learning functions
  5. Natural language processing capabilities
  6. Can be used for applications like data analysis, modeling, education, research, engineering, finance, and more.

Pricing

  • Subscription-Based
  • Volume Licensing Available
  • Free Trial Version

Pros

Very powerful and versatile for technical computing

Intuitive syntax and workflows

Excellent graphics, plotting, and visualization capabilities

Can handle both symbolic and numeric computations

Has many built-in algorithms, models, and datasets

Can automate complex tasks and workflows

Integrates well with other systems and languages

Cons

Steep learning curve

Expensive proprietary software

Not open source

Not as fast as lower-level languages for some numerical tasks

Limited applications outside of technical fields

Not as popular for general programming compared to Python, R, etc.