CATIA vs OpenMDAO
CATIA
3ds.comOpenMDAO
openmdao.orgSide by side
| Figure | CATIA | OpenMDAO |
|---|---|---|
| Price from | $544.75/mo | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| Linux | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Generative Design Software | 8.3 (#1) | 7.6 (#10) |
| Purpose | CATIA supports imagining, designing, and simulating new products and systems. | OpenMDAO is an open-source Python framework for systems analysis and multidisciplinary optimization. |
Plans
CATIA
- CATIA for Architecture, Engineering & Construction — Yearly Subscription$6,537 a year
In their own words
CATIA
CATIA is a parametric modeling and engineering product with tools for assembly design, sheet-metal work, and surface modeling. It supports cloud collaboration. Platform availability depends on the CATIA product: browser applications run on the 3DEXPERIENCE platform, while CATIA V5 sheet-metal software is available for Windows. File format support also varies by product. STEP import and export are listed, while DXF, STL, VRML, and IGES are supported by other CATIA V5 products. CATIA is paid, with pricing on request. Buyers should match the intended modeling work, collaboration needs, platform, and file exchange requirements to the specific CATIA product. Its web and Windows listings do not mean that every CATIA capability is offered on both platforms.
OpenMDAO
OpenMDAO is a free, open-source Python framework for systems analysis and multidisciplinary optimization, available for Linux and self-hosted use. It focuses on gradient-based optimization with analytic derivatives, including design spaces with hundreds or thousands of variables. Models combine components and groups, while drivers run optimization algorithms or design of experiments. Nonlinear and linear solvers can be positioned at different levels of the model hierarchy. Derivative tools include analytic partial derivatives, finite-difference and complex-step approximations, derivative checking, and forward or reverse total derivative calculations. MPI features support parallel subsystems and distributed variables across processes. Parallel computing can also support gradient-free optimization, mixed-integer nonlinear programming and design space exploration. Users can visualize models and optimization progress, and record or read model and solver cases. Dymos for transient modeling and optimal control, and pyCycle for turbine engine cycle analysis, are identified as related libraries. Installation is documented through PyPI or a cloned GitHub repository. The supported OpenMDAO 3.x line requires Python 3.10 or later; its API may change periodically during active development.