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Java vs Rust: What are the differences?
Java and Rust are two prominent programming languages. Let's explore the key differences between them.
Memory Management: Java uses a garbage collector that automatically handles memory allocation and deallocation. On the other hand, Rust uses a system of ownership, borrowing, and lifetimes, which allows for more controlled and efficient memory management. This enables Rust to provide memory safety without relying on garbage collection.
Concurrency: Java follows a thread-based concurrency model, where multiple threads of execution can be created and run concurrently. Rust, on the other hand, follows an "ownership" based concurrency model, which is thread-safe and allows for efficient concurrency without the risk of data races. This is achieved through Rust's ownership system that enforces strict ownership rules during compilation.
Error Handling: Java and Rust also differ in their approaches to error handling. In Java, exceptions are commonly used for error handling and propagation. In Rust, however, error handling is done through the use of the
Result
type, which forces developers to explicitly handle and propagate errors. This allows for more predictable error handling and reduces the likelihood of runtime exceptions.Maturity and Ecosystem: Java has been around for a longer time and has a larger and more mature ecosystem compared to Rust. Java has extensive libraries, frameworks, and tools that have been developed over the years, making it easier to find resources and solutions for various development tasks. Rust, being a relatively newer language, has a smaller ecosystem but is rapidly growing and gaining traction.
Object-Oriented Programming: While both Java and Rust support object-oriented programming (OOP) principles, the way they approach OOP differs. Java is a fully object-oriented language, where everything is an object and obeys inheritance and polymorphism. Rust, on the other hand, is a multi-paradigm language that offers object-oriented features but puts a greater emphasis on other paradigms like functional programming and pattern matching.
Performance: Java is known for its just-in-time (JIT) compilation and runtime performance optimizations. It is often optimized for throughput and can achieve high performance in certain scenarios. Rust, on the other hand, is a statically-typed language that focuses on low-level control and performance. It compiles to native machine code, enabling developers to write high-performance code with minimal runtime overhead.
In summary, Java is a widely-used, object-oriented programming language known for its portability, scalability, and extensive ecosystem, commonly used for building enterprise-level applications and systems. Rust is a systems programming language known for its safety, concurrency, and performance, favored for building low-level software where control over memory management and thread safety is crucial.
Hello Devs,
I am planning to implement a ETL test system for checking data quality and business use cases. I am confused on what stack to use. Any advice on the below will be very helpful.
- Any existing frameworks and its source code for help
- Any other stack apart from the mentioned stack (that might be suitable)
- Any ideas for features are welcomed.
- The usage of multiple BE stacks.
If you want to create using Python language, Robot Framework is one very helpful tool to improve your test scripting and we have a lot of methods created by the community. If you want to use Javascript, Cypress in terms of benefits is the better option to create and maintain tests, and run and generate reports in many browsers is really easy with them.
I intend to use a programming language which I'll use as AWS runtime and write a script that will comb through tons of files in a directory and its subdirectories and search for simple text regular expressions and process and write the matches in a file as output. I have heard that Perl is good for regex based search but I also want the performance to be good as it will have to go through tons of files for IO. In this post: https://filia-aleks.medium.com/aws-lambda-battle-2021-performance-comparison-for-all-languages-c1b441005fd1, I see that Rust works well as AWS Lambda runtime with very good performance. Which one should I choose as my AWS lambda runtime for this problem? Golang is also an option as it is fast as per the above link.
I used to work in a Perl shop and must admit that the language is very simple for tasks like these, but as you mentioned it's not fast at execution time. I'm now a Go programmer professionally but I taught myself the language while in college purely out of interest and eventually found my way to the job, not the other way around. I've recently been learning a little rust because of how much that language comes up in conversations around Go. I find the concept of the borrow checker nice but I have to admit I feel lost like I am in most flavors of new fancy framework js. That's not to say Rust is really anything like js, but the learning appears the same to me as someone who's convinced they could learn just about any programming language if it was necessary (over time I've seen procedural, OOP, declarative and functional stuff but never programming logic outside of the prolog code I wrote in school).
Go isn't made for your specific task at hand but it's a very easy language to pick up and it has good directory traversal standard library code and good regex (even though with time perl's has been optimized to be faster and I think it's written in C++) but more than anything Go is "cloud native" programming in that an awful lot of new microservice tech stacks are centered around it, docker and kubernetes are written in it, and there's a thriving community whose focus is generally web-first and performance-oriented. This means for your use case there might already be a large cohort of gophers that have asked the stackoverflow questions for you
I personally would push you towards the NYT Profiler for Perl before I would towards Rest, but that's because I know you wouldn't waste any time being able to get to the task at hand and then make it go faster, and I expect all but a few rustaceans would be able to do so with the same speed.
Whatever you pick I wish you the very best of luck!
I will use Elixir for personal projects. It's productive, reliable, secure, simple, etc. But when performance is critical, I need job opportunities, when I work with mutability, which do I pick? I need advice on which "bureaucratic, mainstream" programming language to pick when wanting performance and jobs. Elixir is often "slow", and it hasn't boomed yet the way Golang and Rust have, so which?
Well for those performant tasks maybe you can use Rust nifs for elixir. Elixir enables to write fault-tolerant, scalable code for concurrent systems, and as such, it is perfect for messaging systems and web applications that might need to handle a lot of users efficiently. But if you need speed you can plug in Rust or write a microservice using Goland/Rust.
Hello Folks, my first time here, and for requesting advice. I am trying to create some automation from my cloud stack on AWS to something more cloud native. I have containerised the services, however, I am stuck at DB, my Data warehouse, and messaging. Would love some recommendations on how can I automate this for some future work too.
I recommend cloud-init for base setup of machines and configuring them.. Its simple (YAML file) and is industry standard. Even works on bare metal as well as cloud.
I've been working with Js/Ts as a backend developer and I would like to get some suggestions about what new language to learn right now. I've been thinking about Elixir or Rust, focusing on creating WebApis and Blockchain technology. I am passionate about the funcional way but I'm now confident about Elixir in Blockchain. Rust seems like have more jobs about it than Elixir in a little research. Someone could give me some advice? Thank you.
For web development I would suggest to take a look into Elixir. Elixir is extemely good for real time apps through websockets, apps with a need of high concurrency and / or apps where you need to process hundreds of thousands of states of differents users in parallel thanks to the actor model that comes with Erlang virtual machine. To solve these kind of problems in another stack could be really hard and painful (including your current stack).
It's true that Elixir is a niche stack ( It deserves way more popularity in my opinion), so, if your concern is to learn something that would keep you inside the trend and market, instead of Rust or Elixir I would suggest Go. Go it's another outstanding language, will a lot of virtues, small and easy to learn, with it for example, you could compile the same application to different operating systems just with a special compiler command (And the compiler is blazing fast). You can also start with a lot of good libraries that helps you to keep your code clean and under control and of course, it's performance is very good too.
Hope my suggestions could be helpful.
Best regards, and happy coding!
Golang is to my mind by far the greatest bang for your buck in terms of investing your time it has a low barrier to entry. Elixir is fun and all, but it is VERY VERY niche. You are very unlikely to find a job directly requiring Elixir. Rust is a good option depending on what you want to achieve but golang is a great general-purpose language that has a very approachable learning curve, great documentation and a lot of jobs available. There are some very high profile projects written in golang. Docker, Kubernetes, InfluxDB and Grafana just to name a few. I was at this same junction at the end of 2018 having spent a lot of time in JS/TS & Ruby. I had already learned Elixir and done a couple of projects in it and I switched to Golang as I didn't want to learn niche languages. I have never regretted my choice. Obviously, every tool has its place but golang is a winner if you want to learn something new :)
Hi, I am working as a web developer (PHP, Laravel, AngularJS, and MySQL) with more than 8 years of experience and looking for a tech stack that pays better. I have a little bit of knowledge of Core Java. For better opportunities, Should I learn Java, Spring Boot or Python. Or should I learn Drupal, WordPress or Magento? Any guidance would be really appreciated! Thanks.
Hard to answer it depend on market. Python + Flask + Jinja2 is better that SpringBoot. Java can be paid better now but I think that future is Python. I code very good in PHP, Java, Python - prefer Python for less code and more effects. PHP is little ugly and limited to web.
What do you think about Node JS with React? I feel like this stack is fairly paid more than PHP.
I am also a Laravel developer, in process of transitioning towards Node js.
If you wanna personally connect with me, hit me up at @izshreyansh on twitter.
Actually, I'll add, C++ and C# as well.
Well, I'm into Computer Science since 1996, so I understand a bit of everything plus a lot of different OSs, I study 10 hours per day every day. However back in the 90s we didn't have books or universities about programming, all were passed through if you knew somebody in that profession. Which I did and in that time, he showed me .NET and MySQL, and that offered a lot of jobs also Java. Today you have a lot of options but I'm already discarding new languages as I believe they will jot succeed.
My always dream was to create game, and software. I don't understand all programming concepts and I'm studying all languages at the same time, so I'm heavy loaded. But that keeps me more aware.
I made a choice: use Python for everything but if you want performance, apps, security, compatibility, Multiplatform. What should I choose? The real question here is: which language should I go 100% and that language will teach me all I need about programming BUT without getting lost in that language forever (I discard any Assembly possibility) and one that has full documentation, support and libraries.
In my experience: I found a lot of info for python and java. But hardly I have ever found anything for C lang, C++ and, what about C# (it's only for Windows, is it easy, I saw a lot of documentation). Thanks!!
Python can be linked with C++ both language are similar in many places (using same libraries or concepts to build libraries) - except memory and static types. C++ is more assembler and have different syntax (need 3x-4x coding more).
If you do engineering it is perfect stack - Java is to slow in coding (4x more code) and little faster than Python - whatever it is hard to mix Java/C++ what is easy Python/C++.
In the most program you do not need super performance but if you need C++ is the best and have rich Object Language much richer than Java and more poor than Python. Python is true object language - everything is object.
Whatever sometimes more important is framework than language for specific use.
I would go with Python, it is fast to code, readable and very powerful without giving you too much to think about (e.g. memory management). If you're looking for speed, Cython is a fairly good way to get there, since Python is a C-based language it can be compiled to C using Cython and will get you a very significant boost in speed! You can also make use of C libraries if you prefer. The only downside to Cython over Python is that it is compiled and not interpreted, which can make debugging a pain (but you might find yourself doing most of the debugging in Python before switching to Cython). C languages are a bit of a pain to read up on (API, libraries etc.), but Stack Overflow has you covered in most cases!
All programming languages are cross platform except Java, but even that's not that bad. Performance: C(++), Go, Rust, Java, Ada, OCaml, Haskell, C# Apps: JS, TS, ReScript, Go, C(++), Java, Haskell, C#, Dart Security: Java, Go, Rust, COBOL, C(++), C# Compatibility: Java(due to it's VM), C(++), Go, C# Libraries: Java, Go, C(++), C# Documentation: Java, C(++) (since they are mature) What do you mean without getting lost in the language? I'd not advocate for C(or C++), considering it's hard to understand the memory, and it's for those into programming theory. You are looking for all you need. Go for Java, it has a library for everything, it has a reasonable learning curve, and pretty much you are going to encounter it everywhere- it's like a programming black hole you can't escape.
When working on Python, I noticed that Python is only useful for data science. I am looking for a programming language that:
Is different in terms of paradigm(I used OO only in Python for data analysis, I want something that is a different paradigm to improve my coding skills)
Is excellent at systems engineering
Will enhance my Python projects and basically make Python better
Has an excellent future, will skyrocket in terms of demand
Is very performant, excellent performance
Has a steep learning curve(it's because I want a simple language and an advanced language in my stack)
I found these two languages to fit my needs, and I need help choosing. Which would be better for me considering my needs
Rust is more useful compared to C on some cases like in web assembly. C is more tedious to code. Rust is modern and has a lot more of opportunities. If you are also investing for the future I recommend Rust over C.
It must be Rust, It absorbs the advantages of other languages,safe, good performance and develop quickly, The community is also growing and active. I think there are some difficulties to learn Rust, but when you have mastered it, you will write good programs than C lang
Generally speaking, what are the most important things you expect a junior developer to know and be able to do from day 1 in your respective tech stack? Firm grasp of OOP? SQL? MVC? ORM? Algorithms and Datastructures? Understanding CRUD & the request response cycle? Database design? framework familiarity? Postman? Deployment? TDD? Git? Language-specific knowledge? Other things?
Start with building a solid understanding of computer science fundamentals. Understand the basics of building blocks - memory, processing, storage, networking. Understand what CPU bound, memory bound, I/O bound, network bound processes are. Understand the cost of accessing data from Memory vs. Disk vs Network. Understand how multiple CPU threads help in optimizing the performance of a single machine.
Build expertise on a programming language. You may pick any language of your choice. I would recommend starting with Java / Python. Make sure you know one language really well. Build a strong understanding of Data Structures and Algorithms. You should be able to develop an intuition on when to use what. You may practice DS and Algorithm problems, using the language of your choice, on a competitive coding platform (e.g. Leetcode) or by building your own App!
Next, get familiar with basic cloud computing and distributed system concepts. Here is a good resource for that - https://www.youtube.com/watch?v=p7NkTUyEE1o&ab_channel=JeffreyRichter If you understand the computer science fundamentals well, you will be able to apply those concepts here as well.
Hope it helps!
Ability to read code and willingness to try to reason flow of operations and information. Tools and technologies change, one doesn't need to have them in toolbelt from day one. All things you name are relevant in some contexts, so it's not bad to understand them.
Just learn to learn. Learn to search and develop your logical thinking, that's all you need. No books, no deep study of how computers work, just logic and willingness to learn
For me, it is less of a specific technology you know (although I would prefer you have some knowledge of some of my team stack). It is more the way you get into a problem, the eagerness to learn more, the true sincerity to say "I don't know", the open mind to find solutions in different ways and the "Yes we can" mentality no matter how hard it is.
Most employers don't expect from you to know how to implement CI/CD or any other funcy stuff. As junior developer you should focus on building a good toolset of good software practices & principles. Your soft skills are important as well. Learn about soft skills. Be eager to learn, be humble and show you talent and your creativity through your work. If you want to become a good developer ( at first) and a star engineer (at a later stage) then computer programming (coding) is your number one priority . Coding is like painting. Putting aside your talent, you have to practice a lot and improve your outcome each time. As junior developer you can learn how to write good code by studying existing code found in public git repositories (i e , github). As junior developer you should study some good software principles (i.e., DRY, KISS, YAGNI) and always recall them each time you write software code. As junior developer you should learn about coding standards and conventions. You will have to follow to your company's coding conventions (soon or later) as well as you will realize that you have to write code cosistent to the existing code base. At the end of the day, code consistency matters a lot. You have to improve your code day by day. If you manage to follow some good software practices you will find out that you will need an ORM to work with your database. Then you will realize that you need the X web framework to build your REST API etc. To sum up, you will start building a toolset with a single programming language and some good software practices & principles and then you will put new tools in it day-by-day.
Hey there, we are looking to develop our own layer 1 blockchain. We're splitting the responsibilities for origination, clearing, and settlement across three independent but cooperating node networks. We've gotten our Proof of Concept up using Ruby on Rails for the nodes, you can see it as the attached link. So far, so good. Now we are looking to convert it into a distributable and are trying to figure out which language is the best for this.
Essentially our needs from the language are: solid networking tools and speed, very fast execution of basic actions, some parallel execution, and able to compile the end product into an easy to distribute and use package for end users.
I was learning Rust, but I have a healthy amount of experience with Swift and right now, it's only me coding. I've only done iOS coding, but have built a fintech app from scratch that's now in the app store so I'm pretty familiar with the language and its benefits. Haven't experimented with Vapor or any of the application development tools, and I wanted to know if it is a crazy idea to develop a blockchain node in Swift instead.
Pick Rust. Rust can provide all what you need and has been a major language in blockchain/cryptocurrency industry. Swift is slower than Rust and does not have such support in the networking and domain field. Swift tooling is great only on macOS, therefore you are likely to have troubles on other platforms.
You can use swift of course. It’s more of a question of being performant.
You really want to try some basic operations and find what’s most performant for you.
Rust is wonderful for cloud applications requiring heavy concurrency, it has compile time checking for such things.
Go and C++ could be more performant in your case. Swift is really quite an obtuse language, with a lot of features, some which may complicate your implementation.
Also, you want to consider the market of developers who could help build it. If you use Go or C++ there is a larger collection of people who know the languages than there is with swift.
We're moving from Java to Kotlin with our Microservice Stack (Spring Boot) because it is excellently supported by framework and tools and the learning curve is not very steep Kotlin is way more straightforward and convenient to use while providing less boilerplate and more strictness, which finally leads to better code, which is more readable, maintainable and less error-prone. We especially like Kotlin's (functional) data structures, which are, e.g. compared to Scala, easier to understand and don't require deep knowledge in functional programming.







We have chosen a mix of Java and Python for building an open source data observability tool. The application can work as a standalone command line tool with a rich shell interface (using even command completion). The Java ecosystem is more mature when it comes to connectivity to various databases using JDBC. Also picocli with jline3 let us make a very dynamic shell interface with command completion. The definitions of data quality checks that should be executed are defined in YAML files, backed by a YAML (in fact JSON) schema files. Our YAML files can be edited in Visual Studio Code (and other code editors) with support of the code completion. It is possible because all the data model is defined as pure Java classes for which we are generating a YAML/JSON schema. There is still place for Python because it is very popular in the database space. We are simply starting a Python interpreter in the background (from a Java code). Python is used to evaluate validation rules (defined as Python functions) and render SQL queries from Jinja2 templates.
I wanted to develop a student app that possibly could be used by many teams (students from other schools)
I chose Ionic, because:
single codebase: previously, we used React Native for Android and Angular for web/PWA, which was troublesome
portability: runs on PWA (which is important, because iOS license is too expensive for school app), web, Android iOS (+ others, if needed)
full use of web technologies: Next.js, Tailwind, React in this example (in oppose to Flutter/Java/Kotlin)
stability and maintainability: low-entry level due to basic web technologies without new syntax (in oppose to React Native and Flutter), web is really stable and won't lose support (which doesn't have to be true with Flutter/Dart)
We chose Rust for our web API because the Warp crate makes it easy to compose high-performance and asynchronous APIs. Rust allows us to achieve high development velocity because it provides zero-cost abstractions and enforces strict type and memory-safety checks with high quality and actionable error messages.
Expo was a tool Macombey really wanted to utilize from the beginning. I have been working with React Native since 2016 and originally I had to use simulators in Xcode, install pods on top of node packages, configure certificates, and more abundant objectives that take time away from actual development. As a development studio, we have to move quick and get projects to our clients and partners in a matter of months.
Expo made this easy for us. We now have a mobile app for clients to download and test their project on, there is no need to install pods or configure Xcode, and development is super fast and reliable now.
I had a goal to create the simplest accounting software for Mac and Windows to help small businesses in Canada.
This led me to a long 2 years of exploration of the best language that could provide these features:
- Great overall productivity
- International wide-spread usage for long-term sustainability and easy to find documentation
- Versatility for creating websites and desktop softwares
- Enjoyable developper experience
- Ability to create good looking modern UIs
- Job openings with this language
I tried Python, Java, C# and C++ without finding what I was looking for.
When I discovered Javascript, I really knew it was the right language to use. Thinking of this today makes me realize even more how great a decision this has been to learn, use and master Javascript. It has been a fun, challenging and productive road on which I am still satisfied.
Obviously, when I refer to Javascript, it is not without implying the vast ecosystem around it. For me, JS is a whole universe in which almost every imaginable tools exist. It's awesome - for real. Thanks to all the contributors which have made it possible.
To be even clearer about how intense I am with Javascript, let's just say that my first passion was music. Until, I find coding with Javascript! Yep, I know!
So in conclusion, I chose Javascript because it is versatile, enjoyable, widely used, productive for both desktop softwares and websites with ability to create modern great looking user interfaces (assuming HTML and CSS are involved) and finally there are job openings.
#rust #elixir So am creating a messenger with voice call capabilities app which the user signs up using phone number and so at first i wanted to use Actix so i learned Rust so i thought to myself because well its first i felt its a bit immature to use actix web even though some companies are using Rust but we cant really say the full potential of Rust in a full scale app for example in Discord both Elixir and Rust are used meaning there is equal need for them but for Elixir so many companies use it from Whatsapp, Wechat, etc and this means something for Rust is not ready to go full scale we cant assume all this possibilities when it come Rust. So i decided to go the Erlang way after alot of Thinking so Do you think i made the right decision?Am 19 year programmer so i assume am not experienced as you so your answer or comment would really valuable to me
Python has become the most popular language for machine learning right now since almost all machine learning tools provide service for this language, and it is really to use since it has many build-in objects like Hashtable. In C, you need to implement everything by yourself.
C++ is one of the most popular programming languages in graphics. It has many fancy libraries like eigen to help us process matrix. I have many previous projects about graphics based on C++ and this time, we also need to deal with graphics since we need to analyze movements of the human body. C++ has much more advantages than Java. C++ uses only compiler, whereas Java uses compiler and interpreter in both. C++ supports both operator overloading and method overloading whereas Java only supports method overloading. C++ supports manual object management with the help of new and delete keywords whereas Java has built-in automatic garbage collection.
Context: Writing an open source CLI tool.
Go and Rust over Python: Simple distribution.
With Go and Rust, just build statically compiled binaries and hand them out.
With Python, have people install with "pip install --user" and not finding the binaries :(.
Go and Rust over Python: Startup and runtime performance
Go and Rust over Python: No need to worry about which Python interpreter version is installed on the users' machines.
Go over Rust: Simplicity; Rust's memory management comes at a development / maintenance cost.
Go over Rust: Easier cross compiles from macOS to Linux.
We have a lot of experience in JavaScript, writing our services in NodeJS allows developers to transition to the back end without any friction, without having to learn a new language. There is also the option to write services in TypeScript, which adds an expressive type layer. The semi-shared ecosystem between front and back end is nice as well, though specifically NodeJS libraries sometimes suffer in quality, compared to other major languages.
As for why we didn't pick the other languages, most of it comes down to "personal preference" and historically grown code bases, but let's do some post-hoc deduction:
Go is a practical choice, reasonably easy to learn, but until we find performance issues with our NodeJS stack, there is simply no reason to switch. The benefits of using NodeJS so far outweigh those of picking Go. This might change in the future.
PHP is a language we're still using in big parts of our system, and are still sometimes writing new code in. Modern PHP has fixed some of its issues, and probably has the fastest development cycle time, but it suffers around modelling complex asynchronous tasks, and (on a personal note) lack of support for writing in a functional style.
We don't use Python, Elixir or Ruby, mostly because of personal preference and for historic reasons.
Rust, though I personally love and use it in my projects, would require us to specifically hire for that, as the learning curve is quite steep. Its web ecosystem is OK by now (see https://www.arewewebyet.org/), but in my opinion, it is still no where near that of the other web languages. In other words, we are not willing to pay the price for playing this innovation card.
Haskell, as with Rust, I personally adore, but is simply too esoteric for us. There are problem domains where it shines, ours is not one of them.
Pros of Java
- Great libraries605
- Widely used446
- Excellent tooling401
- Huge amount of documentation available396
- Large pool of developers available334
- Open source209
- Excellent performance203
- Great development158
- Used for android150
- Vast array of 3rd party libraries148
- Compiled Language61
- Used for Web53
- High Performance47
- Managed memory46
- Native threads45
- Statically typed43
- Easy to read35
- Great Community33
- Reliable platform29
- Sturdy garbage collection24
- JVM compatibility24
- Cross Platform Enterprise Integration22
- Good amount of APIs20
- Universal platform20
- Great Support18
- Great ecosystem14
- Lots of boilerplate11
- Backward compatible11
- Everywhere10
- Excellent SDK - JDK9
- Static typing7
- Cross-platform7
- It's Java7
- Mature language thus stable systems6
- Better than Ruby6
- Long term language6
- Portability6
- Clojure5
- Vast Collections Library5
- Used for Android development5
- Best martial for design4
- Most developers favorite4
- Old tech4
- Javadoc3
- History3
- Testable3
- Great Structure3
- Stable platform, which many new languages depend on3
- Type Safe2
- Faster than python2
- Job0
Pros of Rust
- Guaranteed memory safety145
- Fast132
- Open source88
- Minimal runtime75
- Pattern matching72
- Type inference63
- Algebraic data types57
- Concurrent57
- Efficient C bindings47
- Practical43
- Best advances in languages in 20 years37
- Safe, fast, easy + friendly community32
- Fix for C/C++30
- Stablity25
- Zero-cost abstractions24
- Closures23
- Great community20
- Extensive compiler checks20
- No NULL type18
- Async/await18
- Completely cross platform: Windows, Linux, Android15
- No Garbage Collection15
- Great documentations14
- High-performance14
- High performance12
- Generics12
- Super fast12
- Fearless concurrency11
- Guaranteed thread data race safety11
- Safety no runtime crashes11
- Compiler can generate Webassembly11
- Macros11
- Helpful compiler10
- RLS provides great IDE support9
- Easy Deployment9
- Prevents data races9
- Painless dependency management8
- Real multithreading8
- Good package management7
- Support on Other Languages5
- Type System1
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Cons of Java
- Verbosity33
- NullpointerException27
- Nightmare to Write17
- Overcomplexity is praised in community culture16
- Boiler plate code12
- Classpath hell prior to Java 98
- No REPL6
- No property4
- Code are too long3
- Non-intuitive generic implementation2
- There is not optional parameter2
- Floating-point errors2
- Java's too statically, stronglly, and strictly typed1
- Returning Wildcard Types1
- Terrbible compared to Python/Batch Perormence1
Cons of Rust
- Hard to learn28
- Ownership learning curve24
- Unfriendly, verbose syntax12
- High size of builded executable4
- Many type operations make it difficult to follow4
- No jobs4
- Variable shadowing4
- Use it only for timeoass not in production1