C++ vs Spring Boot: What are the differences?
Developers describe C++ as "Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation". C++ compiles directly to a machine's native code, allowing it to be one of the fastest languages in the world, if optimized. On the other hand, Spring Boot is detailed as "Create Spring-powered, production-grade applications and services with absolute minimum fuss". Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can "just run". We take an opinionated view of the Spring platform and third-party libraries so you can get started with minimum fuss. Most Spring Boot applications need very little Spring configuration.
C++ belongs to "Languages" category of the tech stack, while Spring Boot can be primarily classified under "Frameworks (Full Stack)".
"Performance", "Control over memory allocation" and "Cross-platform" are the key factors why developers consider C++; whereas "Powerful and handy", "Easy setup" and "Java" are the primary reasons why Spring Boot is favored.
Spring Boot is an open source tool with 39.8K GitHub stars and 25.8K GitHub forks. Here's a link to Spring Boot's open source repository on GitHub.
According to the StackShare community, Spring Boot has a broader approval, being mentioned in 333 company stacks & 616 developers stacks; compared to C++, which is listed in 199 company stacks and 371 developer stacks.
What is C++?
What is Spring Boot?
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Ruby NLP C++ Grammar #BNF
At FriendlyData we had a Ruby-based pipeline for natural language processing. Our technology is centered around grammar-based natural language parsing, as well as various product features, and, as the core stack of the company historically is Ruby, the initial version of the pipeline was implemented in Ruby as well.
As we were entering the exponential growth phase, both technology- and product-wise, we looked into how could we speed up and extend the performance and flexibility of our [meta-]BNF-based parsing engine. Gradually, we built the pieces of the engine in C++.
Ultimately, the natural language parsing stack spans three universes and three software engineering paradigms: the declarative one, the functional one, and the imperative one. The imperative one was and remains implemented in Ruby, the functional one is implemented in a functional language (this part is under the NDA, while everything I am talking about here is part of the public talks we gave throughout 2017 and 2018), and the declarative part, which can loosely be thought of as being BNF-based, is now served by the C++ engine.
The C++ engine for the BNF part removed the immediate blockers, gave us 500x+ performance speedup, and enabled us to launch new product features, most notably query completions, suggestions, and spelling corrections.
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
Maybe not in everybody focus but I do like programming for @z/OS, @z/Linux and @z/VM with C++ , Java and Assembler . Who else love to dig into control blocks and get a deep dive into system resources to run things in a high valuable way ? And also go all the way up to the application to enlight all the infrastructure features to it ?
Initially, I wrote my text adventure game in C++, but I later rewrote my project in Rust. It was an incredibly easier process to use Rust to create a faster, more robust, and bug-free project.
One difficulty with the C++ language is the lack of safety, helpful error messages, and useful abstractions when compared to languages like Rust. Rust would display a helpful error message at compile time, while C++ would often display "Segmentation fault (core dumped)" or wall of STL errors in the middle. While I would frequently push buggy code to my C++ repository, Rust enabled me to only even submit fully functional code.
Along with the actual language, Rust also included useful tools such as rustup and cargo to aid in building projects, IDE tooling, managing dependencies, and cross-compiling. This was a refreshing alternative to the difficult CMake and tools of the same nature.
I use Spring-Boot because it almost let you get things done quickly for a JVM-target project, with auto configuration components and dependency management starters. It is almost perfectly tailored for microservices applications development with a single unit deployment artifact (JAR) along with support for Service Registry and Discovery, Circuit Breaker pattern...
Any third-party library or any back-end service would perfectly integrate well since Spring offers integration support for most of mainstream services, let it be a RDBMS service, a NoSQL database, a Message Broker...
Coming to day-to-day development, Spring-Boot enjoys a great community so you can get support, direction, focused guidance from almost everywhere.
We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.
To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas
To build #Webapps we decided to use Angular 2 with RxJS
#Devops - GitHub , Travis CI , Terraform , Docker , Serverless
At FlowStack we write most of our backend in Go. Go is a well thought out language, with all the right compromises for speedy development of speedy and robust software. It's tooling is part of what makes Go such a great language. Testing and benchmarking is built into the language, in a way that makes it easy to ensure correctness and high performance. In most cases you can get more performance out of Rust and C or C++, but getting everything right is more cumbersome.
spring boot allow my team to start building web services quickly and package it in a stand alone application
C++ is used in Shiro (https://github.com/Marc3842h/shiro).
C++ is a high performance, low level programming language. Game servers need to run with fast performance to be able to reliably serve players across the globe.
The most latency sensitive parts are written in C++. Due to our interconnected services architecture, we use either Python or C++ for each service, with the performance critical parts being C++14.
Spring-Boot allows us to create stand-alone web servers and helps us configure many of our dependencies with sane default, while maintaining flexibility where we need it.
Used to write PHP extensions - AZTEC Decoder - License Driver scan - Axis2/C to PHP wrapper and Job-scheduler - Barbershop
Performance, zero-overhead abstractions and memory safety of the modern C++ language make this the perfect language for the project.
The main programming language of ApertusVR. C++11 & CMake provides multi-platform targeting. The architecture is modular.