Julia
MATLAB
Python
GNU Octave
Rust
Wolfram Mathematica
Clojure
Scilab
Modelence
Lovable
Floot
BASE44
Getting MEAN with MEMEs
Supabase
HTML and CSS: Interactive Projects
Convex.dev
We recommend LibHunt Julia for discovery and comparisons of trending Julia projects.
Modelence is a no-code app builder that helps you build real, production-ready web apps (not prototypes) with everything you need to go live by default. It lets users build complete web applications with built-in authentication, database, and monitoring - all in one platform. Powered by its own open-source library designed specifically for the AI era, Modelence enables fast, reliable app development without writing a single line of code. Whether you're building internal tools, SaaS products, or MVPs, agents handle the entire development process from start to deployment. Once live, you can easily scale your app and monitor its performance and metrics in real time. Modelence is free to get started and supports the full app lifecycle out of the box.
Julia Modelence{"data_science" => "Data scientists who require a fast and flexible language for data manipulation and analysis.", "machine_learning" => "Developers looking to implement machine learning models that benefit from Julia's performance.", "numerical_analysis" => "Engineers and analysts conducting numerical analysis that demands high computational efficiency.", "scientific_computing" => "Researchers and scientists working on mathematical, statistical, and computational problems."}
Modelence's answer:
TypeScript and MongoDB as the core stack, built on Modelence's own open-source full-stack framework. The AI App Builder layer handles prompt-to-app generation on top of this foundation.
Modelence's answer:
Compared to Lovable, Replit, or Base44, Modelence gives you production-grade apps (not throwaway prototypes), a fully open-source codebase you can eject and self-host anytime, and a streamlined no-code experience backed by a robust full-stack framework.
Modelence's answer:
Non-technical founders, solo entrepreneurs, and small teams who need to ship real software products quickly - without hiring a dev team or learning to code. Also appeals to technical users who want to accelerate app development with AI while retaining full code access.
Modelence's answer:
Modelence builds real, production-ready apps from prompts - not just prototypes. Unlike other AI app builders, it's powered by an open-source TypeScript/MongoDB framework, so you get full code ownership and no vendor lock-in.
Based on our record, Julia seems to be more popular. It has been mentiond 130 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you're looking for a language that aims to solve the "two-language problem" like Mojo, but want something more open, more mature and less influenced by VC funding, check out Julia: https://julialang.org/. - Source: Hacker News / 2 months ago
The problem with MATLAB is that idiomatic MATLAB style (every operation returns a fresh matrix) can easily become very inefficient: it leads to countless heap memory allocations of new matrices, resulting in low data-access locality, i.e. Your data is needlessly copied around in slow DRAM all the time, rather than being kept in the fastest CPU cache. Julia's MATLAB-inspired syntax is at least as nice, but the... - Source: Hacker News / 7 months ago
In this post, We will learn how to simulate MRI physics In the Julia programming language, a free and open source programming language That excels especially in scientific computing. - Source: dev.to / 9 months ago
Mine is Julia, although I don't use diary. Nowadays I like SuperCollider. https://julialang.org. - Source: Hacker News / about 1 year ago
> I was active in the Python community in the 200x timeframe, and I daresay the common consensus is that language didn't matter and a sufficiently smart compiler/JIT/whatever would eventually make dynamic scripting languages as fast as C, so there was no reason to learn static languages rather than just waiting for this to happen. To be very pedantic, the problem is not that these are dynamic languages _per se_,... - Source: Hacker News / about 1 year ago
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
Lovable - The world's first AI Fullstack Engineer
Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
Floot - Build serious apps with AI without getting stuck
GNU Octave - GNU Octave is a programming language for scientific computing.
BASE44 - The platform for people to turn ideas into working products.
