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Java vs Quarkus: What are the differences?
Introduction
In this article, we will explore the key differences between Java and Quarkus. Java is a widely-used programming language known for its platform independence and object-oriented approach, while Quarkus is a lightweight framework specifically designed for building cloud-native applications.
Execution Model: One of the key differences between Java and Quarkus lies in their execution models. Java follows a traditional, monolithic execution model where the entire application is deployed as a single unit. On the other hand, Quarkus leverages a microservices architecture, allowing for lightweight and modular deployments. This enables Quarkus applications to scale more efficiently and handle high workloads with ease.
Runtime Optimization: Java applications typically require Just-In-Time (JIT) compilation at runtime, which can lead to longer startup times and higher resource usage. In contrast, Quarkus utilizes Ahead-Of-Time (AOT) compilation, which precompiles the application code before it is deployed. This results in significantly faster startup times and lower memory consumption, making Quarkus ideal for serverless and container-based environments.
Developer Productivity: Quarkus offers superior developer productivity compared to traditional Java. With Quarkus, developers can take advantage of live coding capabilities, allowing them to see the changes in real-time without having to restart the entire application. This greatly speeds up the development cycle and makes it easier to iterate on the codebase. Additionally, Quarkus provides a comprehensive set of extensions and tools that simplify the development process even further.
Resource Consumption: Java applications often require a large amount of memory and processing power, which can be challenging in resource-constrained environments. Quarkus, on the other hand, has been optimized to have minimal memory footprint and low CPU usage. This makes it highly suitable for running applications in resource-limited environments such as containers or serverless platforms.
Native Image Compilation: Quarkus introduces the concept of native image compilation, which allows the application to be compiled into a standalone, platform-specific executable. This eliminates the need for a Java Virtual Machine (JVM) at runtime, resulting in faster startup times and reduced memory footprint. This feature is particularly beneficial for serverless environments where cold start times are critical.
Integration with Cloud-Native Technologies: Quarkus provides out-of-the-box integration with popular cloud-native technologies like Kubernetes, Prometheus, and OpenTracing. This makes it easier to deploy and manage Quarkus applications in a cloud-native environment, leveraging the benefits of scalability, resilience, and observability that these platforms offer.
In summary, Quarkus offers a more lightweight, efficient, and developer-friendly alternative to traditional Java for building cloud-native applications. It leverages a microservices architecture, utilizes AOT compilation, provides superior developer productivity, minimizes resource consumption, introduces native image compilation, and integrates seamlessly with cloud-native technologies.
Hi everyone.
I am willing to build a used car sales platform, which will have a lot of stock/photos and will rely a lot on the back end functions and data generating. Java seems to be a good choice, but what other options can I consider that can also be easily scalable as well as a little faster to write?
Thank you
Firstly, you must know that java and python are both amazing languages. But I recommend python mainly because of the variety of modules and packages available to do almost anything. If you are planning on adding graphs, you can use the matplotlib library and to add photos, use the pillow module. And just note that both of these aren't available by default, so you need to install them through pip.
Hi, Kamal! I don't know if your question is still relevant. But I would like to introduce you to our solution, perhaps it will be useful for future projects. We have developed a web application constructor that can be used to create almost any website or application https://falconspace.site/. The entire development stack is reduced to SQL only. The platform is easy to configure and make subsequent changes if necessary.
I am trying to make Roblox game which requires Lua. I quite don't want to go with Lua just because other tools just might let me do more projects later on. I heard that Python is most similar to Lua, but I am still not sure which tool to use. Java, I think it will help me with many stuff later on for websites, projects, and more!
Since you are trying to make a Roblox game, you have no other option than to use Lua, since Roblox only allows coding in Lua. Yes, you've heard right, Python is identical and as easy as Lua, although Lua is easier than Python. Beginning from Lua and then escalating to Python is recommended. Java is only helpful when you are creating a heavy, big-budget, enterprise-level product, otherwise, Python would suffice.
If you really hate lua check out roblox-ts, a tool that compiles typescript code into roblox lua. https://github.com/roblox-ts/roblox-ts
Hi everyone, I have just started to study web development, so I'm very new in this field. I would like to ask you which tools are most updated and good to use for getting a job in medium-big company. Front-end is basically not changing by time so much (as I understood by researching some info), so my question is about back-end tools. Which backend tools are most updated and requested by medium-big companies (I am searching for immediate job possibly)?
Thank you in advance Davit
Go with Python definetly. It's used everywhere by web developers for backend developments : API, website backend, workers... but also by data scientists (lot lot of resources, models and libraries in Python it's language #1). For the web parts, best web framework are in Python : https://stackshare.io/microframeworks (Flask #2 and Django #3). Java is good but trend is not great in terms of popularity amongs developers and tech leaders.
As per my experience java is most wanted for web development as of now. micro service is evolving . with frameworks like spring boot supports rapid development. Spring boot + Docker + kubernetes great combination.
I would recommend learning HTML, CSS, and JavaScript (most important). JavaScript forms the backbone of web development. And, there are many popular and widely used frameworks like Angular and React that heavily rely on the knowledge of JavaScript. The number of job opportunities are much more when it comes to javascript.
I would recommend Python as the programming language and as you are a new developer, Flask to start with. It gives you a solid understanding on the web patterns such as REST and will get you up and running in no time. However, I suggest you to read and study on front-end technologies like (React or Vue) and databases (SQL and NoSQL) and probably some NodeJS as well. First grasp the concepts (which Python is ideal for) then it does not really matter the language as such.
1 code deploys for both: Android and iOS. There is a huge community behind React Native. And one of the best things is Expo. Expo uses React Native to make everything even more and more simple. Awesome technologies. Some other important thing is that while using React Native, you are reusing all JavaScript knowledge you have in your team. You can move easily a frontend dev to develop mobile applications.
A huge PRO of Expo, is that it includes a full building process. You run 1 line in the terminal, and 10 minutes after you have 2 builds done. Double check EAS Expo.
C# and .Net were obvious choices for us at LiveTiles given our investment in the Microsoft ecosystem. It enabled us to harness of the .Net framework to build ASP.Net MVC, WebAPI, and Serverless applications very easily. Coupled with the high productivity of Visual Studio, it's the native tongue of Microsoft technology.
Node.js has been growing in popularity, and the ability to access the global pool of Javascript developers is great. There is a decreased amount of effort for people to work across the frontend and backend, and the language itself is easy and works well for many common use cases.
Go was the other serious candidate, but it just hasn't been implemented in as many Production systems yet, and the best Go engineers I've known have been hackers, whereas we're building a robust analytics platform that requires more caution. Type safety is easily added with TypeScript, and NPM is awesomely handy.
When developing a new blockchain, we as a team chose Go lang over Java and other candidates, due to Go being (a) natively suited to concurrency - there are primitives in the language itself (goroutines, channels) that really help with reasoning about concurrency (b) super fast - build time, running, testing are all much faster that Java, this gives a far superior developer experience (c) shorter and stricter than Java - code is much shorter (less verbose), and there is usually one good way to do things, and even the code formatter that is bundled with Go is very opinionated - over a short time this makes reading other people's code far smoother than having to deal with different styles.
You should be aware that Go presently (v1.13) lacks Generics.
From cross platform development point of view: Using kotlin multiplatform is more convenient than java for implementing cross platform code, since it can be converted to be used in iOS (swift) projects, and it can be easily learned if you already know swift. It still an experimental feature but it helped so far to unify a lot of the common code between our iOS and Android projects. And it is more future proof than java regarding support and maintain multiplatform converting.
We needed to incorporate Big Data Framework for data stream analysis, specifically Apache Spark / Apache Storm. The three options of languages were most suitable for the job - Python, Java, Scala.
The winner was Python for the top of the class, high-performance data analysis libraries (NumPy, Pandas) written in C, quick learning curve, quick prototyping allowance, and a great connection with other future tools for machine learning as Tensorflow.
The whole code was shorter & more readable which made it easier to develop and maintain.
The decision behind choosing a server side technology is never an easy one. Every single language has it's pro's and con's around each.
For me, this decision came down to a couple simple points: 1. Node is a web tech first class citizen, designed around handling web events, in a web technology world 2. Asynchronous
The thing about Python and Java is that they TOO can handle these, and handle these very well. Java for instance powers most of Twitter and Netflix's architecture. Where Python is what's behind giants like Instagram and Patreon. Certainly, you can't go wrong. Heck, Ruby powered GitHub and GitLab, and those things see HUGE traffic.
But this project is a web technology first. And node feels right at home as it itself is a web technology. This decision was more about homogeneous synergy than most anything else. I need it to be screaming fast, asynchronous, and play extremely well with web standards.
Node fits the bill on every front.
I work at Stream and I'm immensely proud of what our team is working on here at the company. Most recently, we announced our Android SDK accompanied by an extensive tutorial for Java and Kotlin. The tutorial covers just about everything you need to know when it comes to using our Android SDK for Stream Chat. The Android SDK touches many features offered by Stream Chat – more specifically, typing status, read state, file uploads, threads, reactions, editing messages, and commands. Head over to https://getstream.io/tutorials/android-chat/ and give it a whirl!
Pros of Java
- Great libraries603
- Widely used446
- Excellent tooling401
- Huge amount of documentation available396
- Large pool of developers available334
- Open source208
- Excellent performance203
- Great development158
- Used for android150
- Vast array of 3rd party libraries148
- Compiled Language60
- Used for Web52
- Managed memory46
- High Performance46
- 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
- Backward compatible11
- Lots of boilerplate11
- Everywhere10
- Excellent SDK - JDK9
- Cross-platform7
- It's Java7
- Static typing7
- Portability6
- Mature language thus stable systems6
- Better than Ruby6
- Long term language6
- Used for Android development5
- Clojure5
- Vast Collections Library5
- Best martial for design4
- Most developers favorite4
- Old tech4
- Testable3
- History3
- Javadoc3
- Stable platform, which many new languages depend on3
- Great Structure3
- Faster than python2
- Type Safe2
- Job0
Pros of Quarkus
- Fast startup13
- Open source13
- Low memory footprint11
- Integrated with GraalVM10
- Produce native code10
- Hot Reload9
- AOT compilation7
- Reactive6
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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 Quarkus
- Boilerplate code when using Reflection2