Software Alternatives & Reviews

Julia Reviews

Julia is a sophisticated programming language designed especially for numerical computing with specializations in analysis and computational science. It is also efficient for web use, general programming, and can be used as a specification language.

Social recommendations and mentions

We have tracked the following product recommendations or mentions on Reddit and HackerNews. They can help you see what people think about Julia and what they use it for.
  • Show HN: Codon: A Compiler for High-Performance Pythonic Applications and DSLs [pdf]
    It depends on the nature of your compute. If it is dominated by IO, or if you are actually calling native libraries (like `numpy` does, or it is something that is handled by `arrow`), there is no reason to switch away from Python. If you are writing custom algorithms, I think https://julialang.org/ is a great option. - Source: Hacker News / 12 days ago
  • Brett Slatkin: Why am I building a new functional programming language?
    Without articulating what particular tradeoffs the author is balancing and sounding like they only recently realized/discovered the parallelism advantage possible to functional programming languages and paradigms, it is hard to know for sure, but I might venture a guess that Julia will be superior to what they build: https://julialang.org. - Source: Hacker News / 19 days ago
  • [D] Assistance Requested: Learning Deep Learning for Graduate Studies in Bioengineering
    On the flip side, if you intend to use anything more sophisticated than a vanilla feedforward or convolutional neural net, the Python frameworks are pretty much going to be your only practical choice. You might also consider using Julia, which may have more familiar syntax if you've used Matlab primarily. - Source: Reddit / 21 days ago
  • Why Python keeps growing, explained
    You should check out Julia (https://julialang.org/), that's very close to what you describe. - Source: Hacker News / 21 days ago
  • Any help or tips for Neural Networks on Computer Clusters
    However, if you are writing numerical code in Fortran and want to be able to better interface it it with machine learning tools and methods, the number one thing I can recommend is to look into Fortran-based automatic differentiation tools. This will enable you to calculate exact derivatives of your code, which are useful to have for training and optimization loops. You can also look into f2py and f90wrap for... - Source: Reddit / 25 days ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    Julia is a general purpose programming language well suited for numerical analysis and computational science. Sometimes it's stated as a future of machine learning and the most natural replacement for Python in this field. - Source: dev.to / about 1 month ago
  • any modern procedural programming languages?
    "dynamically/JIT compiles to LLVM then machine code": but that doesn't define a DSL as far as I know, I don't know Julia (just in my list of wanna learn it) but it does seem to be a full blow programming language https://julialang.org/. - Source: Reddit / about 1 month ago
  • Inventory Run Out in dplyr or data.table
    As an alternative to programmer oriented languages like C++, Julia (https://julialang.org/) is designed to be a data-science oriented language. It has no complicated topics like pointers, references, etc. It is also dynamically typed (just like R so you do not need to explicitly type every variable) but compiled on the fly so you get similar performance with C++ (albeit with a few seconds of start time to... - Source: Reddit / about 2 months ago
  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    In addition to Structured Query Language(SQL), we can also use a variety of different programming languages, such as Python, Java, JavaScript, R, Julia, Scala, or any other programming language as long as it supports a basic database connection and functions to perform all of those operations, to connect to databases and perform more advanced query operations on the data. This gives us greater flexibility and... - Source: dev.to / 2 months ago
  • I am considering returning to attempt another Mathematics M.Sc after failing my first one. I have a few questions to anyone who is willing to listen.
    A state-of-the-art programming language for applied mathematics: https://julialang.org. - Source: Reddit / 3 months ago
  • Why isn’t Go used in AI/ML?
    The Julia folk are trying to build a competitor. They’ve made a promising start but the Python ecosystem and is hard to beat. Also it’s a great REPL environment many data science folk like. - Source: Reddit / 3 months ago
  • Advice on using Calculus in real time
    I would suggest studying numerical analysis. Timothy Sauer's book Numerical Analysis (example link) is a good place to start. It has Matlab exercises, but you can use Julia instead if the Matlab license is too expensive. The languages are very similar. - Source: Reddit / 3 months ago
  • egui 0.20.1 released
    Julia may fit the needs that prompted R originally better than rust, but with a lot of the same improvements (such as based on LLVM). - Source: Reddit / 3 months ago
  • Guido van Rossum on types, speed, and the future of Python
    In many cases it would be sufficient to have a few type annotations combined with type stable code in order for a compiler or type checker to infer most types. Examples for this are https://julialang.org/ and https://numba.pydata.org/ . - Source: Reddit / 3 months ago
  • What other programming language do you actively develop with productively, to complement Python?
    Https://julialang.org/ for non-trivial numerical calculations - mathematical syntax and very high runtime performance. - Source: Reddit / 4 months ago
  • Just a quick question, can a programming language be as fast as C++ and efficient with as simple syntax like Python?
    Yes check out Julia - https://julialang.org/. - Source: Reddit / 4 months ago
  • Just a quick question, can a programming language be as fast as C++ and efficient with as simple syntax like Python?
    Julia comes to mind. Probably not as fast as C++, but feels like python (without the huge userbase and tons of libraries). - Source: Reddit / 4 months ago
  • Matlab alternatives for gradient optimisation problems?
    Julia is also a very good alternative: https://julialang.org/. The syntax is very similar to Matlab. - Source: Reddit / 5 months ago
  • Strongly typed 2D String Array declaration & use???
    I tend to use the latest debian package of things and apt seems to only go to 1.5.3+dfsg-3 version of Julia. I must have downloaded from julialang.org because I'm at 1.6.6. Anyway, downloading 1.8.2 now. Thx. - Source: Reddit / 5 months ago
  • So you're using a weird language
    I'm doing a similar trawl. So far Julia is looking like the language to beat. https://julialang.org/. - Source: Hacker News / 6 months ago
  • Also for all non-programmers in this sub (if any)
    You might like programming in Julia. Using Pluto notebooks is generally excellent too. - Source: Reddit / 6 months ago

External sources with reviews and comparisons of Julia

15 data science tools to consider using in 2021
Julia 1.0 became available in 2018, nine years after work began on the language; the latest version is 1.6, released in March 2021. The documentation for Julia notes that, because its compiler differs from the interpreters in data science languages like Python and R, new users "may find that Julia's performance is unintuitive at first." But, it claims, "once you understand how Julia works, it's easy to write code...
10 Best MATLAB Alternatives [For Beginners and Professionals]
Talking about its capability, Julia can load multidimensional datasets and can perform various actions on them with total ease. Julia has over 13 million downloads as of today. It’s the proof of its flexibility
6 MATLAB Alternatives You Could Use
Strictly speaking, Julia is not a full “alternative” to MATLAB, in the sense that it’s essentially a high-level, dynamic programming language, intended for numerical computing. However, you can easily use it via the free Juno IDE. As for the language itself, it comes with a sophisticated compiler, with support for distributed parallel computing, and a large mathematical function library. And thanks to the active...

Do you know an article comparing Julia to other products?
Suggest a link to a post with product alternatives.