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Go vs Xamarin: What are the differences?

Go: An open source programming language that makes it easy to build simple, reliable, and efficient software. Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language; Xamarin: Create iOS, Android and Mac apps in C#. Xamarin’s Mono-based products enable .NET developers to use their existing code, libraries and tools (including Visual Studio*), as well as skills in .NET and the C# programming language, to create mobile applications for the industry’s most widely-used mobile devices, including Android-based smartphones and tablets, iPhone, iPad and iPod Touch.

Go can be classified as a tool in the "Languages" category, while Xamarin is grouped under "Cross-Platform Mobile Development".

"High-performance", "Simple, minimal syntax" and "Fun to write" are the key factors why developers consider Go; whereas "Power of c# on mobile devices", "Native apps with native ui controls" and "Native performance" are the primary reasons why Xamarin is favored.

Go is an open source tool with 60.5K GitHub stars and 8.37K GitHub forks. Here's a link to Go's open source repository on GitHub.

Uber Technologies, Google, and Medium are some of the popular companies that use Go, whereas Xamarin is used by Olo, Crowdkeep, and GoFormz. Go has a broader approval, being mentioned in 903 company stacks & 609 developers stacks; compared to Xamarin, which is listed in 75 company stacks and 66 developer stacks.

- No public GitHub repository available -

What is Go?

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

What is Xamarin?

Xamarin’s Mono-based products enable .NET developers to use their existing code, libraries and tools (including Visual Studio*), as well as skills in .NET and the C# programming language, to create mobile applications for the industry’s most widely-used mobile devices, including Android-based smartphones and tablets, iPhone, iPad and iPod Touch.
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What are some alternatives to Go and Xamarin?
Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
Rust
Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.
Java
Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!
Node.js
Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
PHP
Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.
See all alternatives
Decisions about Go and Xamarin
PagerDuty
PagerDuty
Slack
Slack
Go
Go
PHP
PHP
Java
Java
Python
Python
Ruby
Ruby
Node.js
Node.js
Sqreen
Sqreen

I chose Sqreen because it provides an out-of-the-box Security as a Service solution to protect my customer data. I get full visibility over my application security in real-time and I reduce my risk against the most common threats. My customers are happy and I don't need to spend any engineering resources or time on this. We're only alerted when our attention is required and the data that is provided helps engineering teams easily remediate vulnerabilities. The platform grows with us and will allow us to have all the right tools in place when our first security engineer joins the company. Advanced security protections against business logic threats can then be implemented.

Installation was super easy on my Node.js and Ruby apps. But Sqreen also supports Python , Java , PHP and soon Go .

It integrates well with the tools I'm using every day Slack , PagerDuty and more.

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Yshay Yaacobi
Yshay Yaacobi
Software Engineer · | 27 upvotes · 270.4K views
atSolutoSoluto
Docker Swarm
Docker Swarm
Kubernetes
Kubernetes
Visual Studio Code
Visual Studio Code
Go
Go
TypeScript
TypeScript
JavaScript
JavaScript
C#
C#
F#
F#
.NET
.NET

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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Tim Abbott
Tim Abbott
Founder at Zulip · | 8 upvotes · 10.4K views
atZulipZulip
Go
Go
Python
Python

We've been a big fan of Python ever since we adopted it for my first startup, Ksplice. But it's been an absolutely ideal tool for Zulip, which is now one of the leading alternatives to Slack. Zulip is 100% open source software, with ~10K stars on GItHub. And being written in idiomatic Python has been really helpful for our open source project, because it's such an accessible language: Any programmer can learn Python quickly. And that means we're not restricted to e.g. "folks who are excited about contributing to Zulip and ALSO know Go".

I've linked to a blog post I wrote on Python's awesome new static type system, which fixes the main complaint one might have about using Python for a large codebase, which has a lot more perspective, as well as some commentary on our Python 3 migration.

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Antonio Sanchez
Antonio Sanchez
CEO at Kokoen GmbH · | 11 upvotes · 85K views
atKokoen GmbHKokoen GmbH
ExpressJS
ExpressJS
Node.js
Node.js
JavaScript
JavaScript
MongoDB
MongoDB
Go
Go
MySQL
MySQL
Laravel
Laravel
PHP
PHP

Back at the start of 2017, we decided to create a web-based tool for the SEO OnPage analysis of our clients' websites. We had over 2.000 websites to analyze, so we had to perform thousands of requests to get every single page from those websites, process the information and save the big amounts of data somewhere.

Very soon we realized that the initial chosen script language and database, PHP, Laravel and MySQL, was not going to be able to cope efficiently with such a task.

By that time, we were doing some experiments for other projects with a language we had recently get to know, Go , so we decided to get a try and code the crawler using it. It was fantastic, we could process much more data with way less CPU power and in less time. By using the concurrency abilites that the language has to offers, we could also do more Http requests in less time.

Unfortunately, I have no comparison numbers to show about the performance differences between Go and PHP since the difference was so clear from the beginning and that we didn't feel the need to do further comparison tests nor document it. We just switched fully to Go.

There was still a problem: despite the big amount of Data we were generating, MySQL was performing very well, but as we were adding more and more features to the software and with those features more and more different type of data to save, it was a nightmare for the database architects to structure everything correctly on the database, so it was clear what we had to do next: switch to a NoSQL database. So we switched to MongoDB, and it was also fantastic: we were expending almost zero time in thinking how to structure the Database and the performance also seemed to be better, but again, I have no comparison numbers to show due to the lack of time.

We also decided to switch the website from PHP and Laravel to JavaScript and Node.js and ExpressJS since working with the JSON Data that we were saving now in the Database would be easier.

As of now, we don't only use the tool intern but we also opened it for everyone to use for free: https://tool-seo.com

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Nitzan Shapira
Nitzan Shapira
at Epsagon · | 11 upvotes · 105.7K views
atEpsagonEpsagon
AWS Lambda
AWS Lambda
GitHub
GitHub
Java
Java
Go
Go
Node.js
Node.js
npm
npm
Serverless
Serverless
Python
Python

At Epsagon, we use hundreds of AWS Lambda functions, most of them are written in Python, and the Serverless Framework to pack and deploy them. One of the issues we've encountered is the difficulty to package external libraries into the Lambda environment using the Serverless Framework. This limitation is probably by design since the external code your Lambda needs can be usually included with a package manager.

In order to overcome this issue, we've developed a tool, which we also published as open-source (see link below), which automatically packs these libraries using a simple npm package and a YAML configuration file. Support for Node.js, Go, and Java will be available soon.

The GitHub respoitory: https://github.com/epsagon/serverless-package-external

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Omar Mehilba
Omar Mehilba
Co-Founder and COO at Magalix · | 13 upvotes · 49K views
atMagalixMagalix
Python
Python
Go
Go
Amazon EC2
Amazon EC2
Google Kubernetes Engine
Google Kubernetes Engine
Microsoft Azure
Microsoft Azure
Kubernetes
Kubernetes
#Autopilot

We are hardcore Kubernetes users and contributors. We loved the automation it provides. However, as our team grew and added more clusters and microservices, capacity and resources management becomes a massive pain to us. We started suffering from a lot of outages and unexpected behavior as we promote our code from dev to production environments. Luckily we were working on our AI-powered tools to understand different dependencies, predict usage, and calculate the right resources and configurations that should be applied to our infrastructure and microservices. We dogfooded our agent (http://github.com/magalixcorp/magalix-agent) and were able to stabilize as the #autopilot continuously recovered any miscalculations we made or because of unexpected changes in workloads. We are open sourcing our agent in a few days. Check it out and let us know what you think! We run workloads on Microsoft Azure Google Kubernetes Engine and Amazon EC2 and we're all about Go and Python!

See more
Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 16 upvotes · 711.8K views
atUber TechnologiesUber Technologies
Apache Spark
Apache Spark
C#
C#
OpenShift
OpenShift
JavaScript
JavaScript
Kubernetes
Kubernetes
C++
C++
Go
Go
Node.js
Node.js
Java
Java
Python
Python
Jaeger
Jaeger

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:

https://eng.uber.com/distributed-tracing/

(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

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Go
Go
Lua
Lua
OpenResty
OpenResty
nginx
nginx
Logstash
Logstash
Prometheus
Prometheus

At Kong while building an internal tool, we struggled to route metrics to Prometheus and logs to Logstash without incurring too much latency in our metrics collection.

We replaced nginx with OpenResty on the edge of our tool which allowed us to use the lua-nginx-module to run Lua code that captures metrics and records telemetry data during every request’s log phase. Our code then pushes the metrics to a local aggregator process (written in Go) which in turn exposes them in Prometheus Exposition Format for consumption by Prometheus. This solution reduced the number of components we needed to maintain and is fast thanks to NGINX and LuaJIT.

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StackShare Editors
StackShare Editors
Kubernetes
Kubernetes
Go
Go
Python
Python

Following its migration from vanilla instances with autoscaling groups to Kubernetes, Postmates began facing challenges while “migrating workloads that needed to scale up very quickly.”

The built-in Horizontal Pod Autoscaler (HPA) automatically scales the number of pods in a replication controller, deployment or replica set based on observed CPU utilization. But the challenges for Postmates is that there’s no way to configure the scale velocity of one particular cluster with an HPA.

For Postmates, which runs at least three different types of applications with distinct performance and scaling characteristics, this proved problematic.

To overcome these challenges, the team created and open sourced the Configurable Horizontal Pod Autoscaler, which allows for fine-grained tuning on a per-HPA object basis. The result is that “you can configure critical services to scale down very slowly, while every other service could be configured to scale down instantly to reduce costs.”

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Git
Git
Docker
Docker
NATS
NATS
JavaScript
JavaScript
TypeScript
TypeScript
PostgreSQL
PostgreSQL
Python
Python
Go
Go

Go is a high performance language with simple syntax / semantics. Although it is not as expressive as some other languages, it's still a great language for backend development.

Python is expressive and battery-included, and pre-installed in most linux distros, making it a great language for scripting.

PostgreSQL: Rock-solid RDBMS with NoSQL support.

TypeScript saves you from all nonsense semantics of JavaScript , LOL.

NATS: fast message queue and easy to deploy / maintain.

Docker makes deployment painless.

Git essential tool for collaboration and source management.

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Vishwa Bhat
Vishwa Bhat
Fullstack Developer at Sequoia · | 10 upvotes · 4.4K views
atSequoia Consulting GroupSequoia Consulting Group
Java
Java
Go
Go
Node.js
Node.js

Our new backend micro services are primarily written in Node.js and Go and legacy systems are written in Java. For our new stack decision, we aimed to achieve greater developer productivity, low IO latency and good community so we had couple of technologies in hand to choose but finally we concluded to go for Node.js for API layer and Go for CPU/IO intensive tasks. Currently the inter-services communication is happening via REST but soon to be moved to RPC-based communication.

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Robert Zuber
Robert Zuber
CTO at CircleCI · | 4 upvotes · 8.6K views
atCircleCICircleCI
Slack
Slack
Go
Go
Hubot
Hubot
CoffeeScript
CoffeeScript

We have added very little to the CoffeeScript Hubot application – just enough to allow it to talk to our Hubot workers. The Hubot workers implement our operational management functionality and expose it to Hubot so we can get chat integration for free. We’ve also tailored the authentication and authorization code of Hubot to meet the needs of roles within our team.

For larger tasks, we’ve got an internal #CLI written in Go that talks to the same #API as Hubot, giving access to the same functionality we have in Slack, with the addition of scripting, piping, and all of our favorite #Unix tools. When the Hubot worker recognizes the CLI is in use, it logs the commands to Slack to maintain visibility of operational changes.

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Greg Neumann
Greg Neumann
Indie, Solo, Developer · | 6 upvotes · 65.8K views
TypeScript
TypeScript
Vue.js
Vue.js
Electron
Electron
Quasar Framework
Quasar Framework
ASP.NET
ASP.NET
Xamarin Forms
Xamarin Forms
.NET Core
.NET Core
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