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MATLAB
MATLAB

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MATLAB vs Rust: What are the differences?

What is MATLAB? A high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.

What is Rust? A safe, concurrent, practical language. Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.

MATLAB and Rust can be categorized as "Languages" tools.

"Simulink" is the primary reason why developers consider MATLAB over the competitors, whereas "Guaranteed memory safety" was stated as the key factor in picking Rust.

Rust is an open source tool with 37.3K GitHub stars and 5.85K GitHub forks. Here's a link to Rust's open source repository on GitHub.

According to the StackShare community, Rust has a broader approval, being mentioned in 39 company stacks & 105 developers stacks; compared to MATLAB, which is listed in 12 company stacks and 23 developer stacks.

- No public GitHub repository available -

What is MATLAB?

Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.

What is Rust?

Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.
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What are some alternatives to MATLAB and Rust?
R
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Octave
It is software featuring a high-level programming language, primarily intended for numerical computations. Octave helps in solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB.
PHP
Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.
JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
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Decisions about MATLAB and Rust
StackShare Editors
StackShare Editors
Rust
Rust
Lua
Lua

To handle its growing observability needs, Postmates created and open sourced Cernan, a telemetry and logging aggregation server. Ceran is built on Rust and Lua, and can ingest data from many sources and then push or exposes what it’s collected to many destinations, or “sinks.” It can also create or manipulate in-flight data with programmable Lua filters.

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James Cunningham
James Cunningham
Operations Engineer at Sentry · | 18 upvotes · 43.5K views
atSentrySentry
Rust
Rust
Python
Python

Sentry's event processing pipeline, which is responsible for handling all of the ingested event data that makes it through to our offline task processing, is written primarily in Python.

For particularly intense code paths, like our source map processing pipeline, we have begun re-writing those bits in Rust. Rust’s lack of garbage collection makes it a particularly convenient language for embedding in Python. It allows us to easily build a Python extension where all memory is managed from the Python side (if the Python wrapper gets collected by the Python GC we clean up the Rust object as well).

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marcoalmeida
marcoalmeida
C
C
Go
Go
Rust
Rust
Python
Python

One important decision for delivering a platform independent solution with low memory footprint and minimal dependencies was the choice of the programming language. We considered a few from Python (there was already a reasonably large Python code base at Thumbtack), to Go (we were taking our first steps with it), and even Rust (too immature at the time).

We ended up writing it in C. It was easy to meet all requirements with only one external dependency for implementing the web server, clearly no challenges running it on any of the Linux distributions we were maintaining, and arguably the implementation with the smallest memory footprint given the choices above.

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Rust
Rust
C++
C++

Initially, I wrote my text adventure game in C++, but I later rewrote my project in Rust. It was an incredibly easier process to use Rust to create a faster, more robust, and bug-free project.

One difficulty with the C++ language is the lack of safety, helpful error messages, and useful abstractions when compared to languages like Rust. Rust would display a helpful error message at compile time, while C++ would often display "Segmentation fault (core dumped)" or wall of STL errors in the middle. While I would frequently push buggy code to my C++ repository, Rust enabled me to only even submit fully functional code.

Along with the actual language, Rust also included useful tools such as rustup and cargo to aid in building projects, IDE tooling, managing dependencies, and cross-compiling. This was a refreshing alternative to the difficult CMake and tools of the same nature.

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Dan Larsen
Dan Larsen
CTO at FlowStack · | 7 upvotes · 26.2K views
atFlowStack ApSFlowStack ApS
C++
C++
C
C
Rust
Rust
Go
Go

At FlowStack we write most of our backend in Go. Go is a well thought out language, with all the right compromises for speedy development of speedy and robust software. It's tooling is part of what makes Go such a great language. Testing and benchmarking is built into the language, in a way that makes it easy to ensure correctness and high performance. In most cases you can get more performance out of Rust and C or C++, but getting everything right is more cumbersome.

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Reviews of MATLAB and Rust
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How developers use MATLAB and Rust
Avatar of Marc3842h
Marc3842h uses RustRust

Rust is used in Shirogane (https://github.com/Marc3842h/shirogane).

Shirogane is a osu! beatmap mirror built for shiro. We use Rust because of memory safe but still low level and high performance.

Avatar of Ralic Lo
Ralic Lo uses MATLABMATLAB

For math calculation and solve partial differential equation numerically.

Avatar of Eliana Abraham
Eliana Abraham uses MATLABMATLAB

I used to be an EE major so you can see where that comes from.

Avatar of Solcast
Solcast uses MATLABMATLAB

Prediction, modelling, and simulation for Solar predictions

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