Alternatives to Apache CXF logo

Alternatives to Apache CXF

Spring, Jersey, Apache Tomcat, Spring MVC, and Apache Camel are the most popular alternatives and competitors to Apache CXF.
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What is Apache CXF and what are its top alternatives?

Apache CXF is an open-source, fully featured web services framework that helps develop SOAP and RESTful services. It supports various protocols and data formats, including JAX-WS and JAX-RS, while providing features like security, WSDL generation, and client/server support. However, its complexity and steep learning curve may be challenging for beginners.

  1. Spring Boot: Spring Boot is a popular Java-based framework that simplifies the development of production-grade applications. It provides a wide range of features for building web services, including support for RESTful services and integration with Apache CXF. Pros: Easy to set up and configure, extensive community support. Cons: Dependency management can be complex for large projects.
  2. Apache Axis2: Apache Axis2 is a versatile web service framework that supports both SOAP and RESTful services. It offers features like WS-Security, WS-ReliableMessaging, and code generation from WSDL files. Pros: Good performance and scalability, strong support for SOAP standards. Cons: Steeper learning curve compared to Apache CXF.
  3. Jersey: Jersey is a reference implementation of JAX-RS (Java API for RESTful Web Services) that simplifies the development of RESTful web services. It provides a lightweight and easy-to-use framework for building RESTful APIs. Pros: Excellent compatibility with Java EE standards, good documentation. Cons: Limited support for SOAP services compared to Apache CXF.
  4. Restlet: Restlet is a lightweight and flexible framework for building RESTful web services in Java. It offers a comprehensive set of features for creating APIs, such as support for various protocols and media types. Pros: Simple and intuitive API design, support for OData. Cons: Limited support for SOAP services, documentation can be improved.
  5. Dropwizard: Dropwizard is a high-performance Java framework for building RESTful web services. It combines various libraries like Jersey, Jackson, and Jetty to provide a streamlined development experience. Pros: Integrated toolset for developing, testing, and deploying web services, good performance. Cons: Limited support for SOAP services, may not be suitable for complex enterprise applications.
  6. Spark: Spark is a lightweight web framework for Java that focuses on simplicity and ease of use. It's ideal for building RESTful APIs and web applications with minimal configuration. Pros: Quick setup and development, suitable for small to medium-sized projects. Cons: Limited built-in features compared to Apache CXF, may not be suitable for complex enterprise applications.
  7. Play Framework: Play Framework is a reactive web framework for Java and Scala that simplifies building web applications and RESTful services. It provides features like hot reloading, asynchronous programming, and integration with Akka. Pros: Strong support for reactive programming, good performance. Cons: Requires learning a new programming model, may not be ideal for traditional enterprise applications.
  8. Dropwizard: Dropwizard is a high-performance Java framework for building RESTful web services. It combines various libraries like Jersey, Jackson, and Jetty to provide a streamlined development experience. Pros: Integrated toolset for developing, testing, and deploying web services, good performance. Cons: Limited support for SOAP services, may not be suitable for complex enterprise applications.
  9. Quarkus: Quarkus is a supersonic subatomic Java framework designed for building cloud-native and serverless applications. It offers impressive startup times, low memory usage, and comprehensive support for popular Java frameworks. Pros: Efficient resource usage, seamless integration with popular Java libraries. Cons: Relatively new in the market, limited community support compared to established frameworks like Apache CXF.
  10. Micronaut: Micronaut is a modern JVM-based framework for building microservices and serverless applications. It is designed for low-memory footprint and fast startup times, making it suitable for cloud-native environments. Pros: Reduced development time, improved performance compared to traditional frameworks. Cons: Limited support for legacy applications, may require learning new programming paradigms.

Top Alternatives to Apache CXF

  • Spring
    Spring

    A key element of Spring is infrastructural support at the application level: Spring focuses on the "plumbing" of enterprise applications so that teams can focus on application-level business logic, without unnecessary ties to specific deployment environments. ...

  • Jersey
    Jersey

    It is open source, production quality, framework for developing RESTful Web Services in Java that provides support for JAX-RS APIs and serves as a JAX-RS (JSR 311 & JSR 339) Reference Implementation. It provides it’s own API that extend the JAX-RS toolkit with additional features and utilities to further simplify RESTful service and client development. ...

  • Apache Tomcat
    Apache Tomcat

    Apache Tomcat powers numerous large-scale, mission-critical web applications across a diverse range of industries and organizations. ...

  • Spring MVC
    Spring MVC

    A Java framework that follows the Model-View-Controller design pattern and provides an elegant solution to use MVC in spring framework by the help of DispatcherServlet. ...

  • Apache Camel
    Apache Camel

    An open source Java framework that focuses on making integration easier and more accessible to developers. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

  • GitHub
    GitHub

    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...

  • Visual Studio Code
    Visual Studio Code

    Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows. ...

Apache CXF alternatives & related posts

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Spring

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CONS OF SPRING
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I am consulting for a company that wants to move its current CubeCart e-commerce site to another PHP based platform like PrestaShop or Magento. I was interested in alternatives that utilize Node.js as the primary platform. I currently don't know PHP, but I have done full stack dev with Java, Spring, Thymeleaf, etc.. I am just unsure that learning a set of technologies not commonly used makes sense. For example, in PrestaShop, I would need to work with JavaScript better and learn PHP, Twig, and Bootstrap. It seems more cumbersome than a Node JS system, where the language syntax stays the same for the full stack. I am looking for thoughts and advice on the relevance of PHP skillset into the future AND whether the Node based e-commerce open source options can compete with Magento or Prestashop.

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Jersey

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    Java Spring JUnit

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        NIDHISH PUTHIYADATH
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        We built our customer facing portal application using Angular frontend backed by Spring boot.

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        A versatile open source integration framework
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          Simon Reymann
          Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.6M views

          Our whole DevOps stack consists of the following tools:

          • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
          • Respectively Git as revision control system
          • SourceTree as Git GUI
          • Visual Studio Code as IDE
          • CircleCI for continuous integration (automatize development process)
          • Prettier / TSLint / ESLint as code linter
          • SonarQube as quality gate
          • Docker as container management (incl. Docker Compose for multi-container application management)
          • VirtualBox for operating system simulation tests
          • Kubernetes as cluster management for docker containers
          • Heroku for deploying in test environments
          • nginx as web server (preferably used as facade server in production environment)
          • SSLMate (using OpenSSL) for certificate management
          • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
          • PostgreSQL as preferred database system
          • Redis as preferred in-memory database/store (great for caching)

          The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

          • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
          • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
          • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
          • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
          • Scalability: All-in-one framework for distributed systems.
          • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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          Tymoteusz Paul
          Devops guy at X20X Development LTD · | 23 upvotes · 10M views

          Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

          It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

          I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

          We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

          If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

          The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

          Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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          Johnny Bell

          I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

          I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

          I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

          Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

          Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

          With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

          If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

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          Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

          Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

          Check Out My Architecture: CLICK ME

          Check out the GitHub repo attached

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            Has better support and more extentions for debugging
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            Excellent as git difftool and mergetool
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            Virtualenv integration
          • 3
            Better autocompletes than Atom
          • 3
            Has more than enough languages for any developer
          • 3
            'batteries included'
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            More tools to integrate with vs
          • 3
            Emmet preinstalled
          • 2
            VS Code Server: Browser version of VS Code
          • 2
            CMake support with autocomplete
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            Big extension marketplace
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            Fast and ruby is built right in
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          CONS OF VISUAL STUDIO CODE
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            Slow startup
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            Resource hog at times
          • 20
            Poor refactoring
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            Poor UI Designer
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            Weak Ui design tools
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            Poor autocomplete
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            Super Slow
          • 8
            Huge cpu usage with few installed extension
          • 8
            Microsoft sends telemetry data
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            Poor in PHP
          • 6
            It's MicroSoft
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            Poor in Python
          • 3
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          Yshay Yaacobi

          Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

          Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

          After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

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          Simon Reymann
          Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.6M views

          Our whole DevOps stack consists of the following tools:

          • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
          • Respectively Git as revision control system
          • SourceTree as Git GUI
          • Visual Studio Code as IDE
          • CircleCI for continuous integration (automatize development process)
          • Prettier / TSLint / ESLint as code linter
          • SonarQube as quality gate
          • Docker as container management (incl. Docker Compose for multi-container application management)
          • VirtualBox for operating system simulation tests
          • Kubernetes as cluster management for docker containers
          • Heroku for deploying in test environments
          • nginx as web server (preferably used as facade server in production environment)
          • SSLMate (using OpenSSL) for certificate management
          • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
          • PostgreSQL as preferred database system
          • Redis as preferred in-memory database/store (great for caching)

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          • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
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          • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
          • Scalability: All-in-one framework for distributed systems.
          • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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