Dart vs Go vs Swift

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Dart
Dart

790
944
+ 1
191
Go
Go

7.7K
6.2K
+ 1
2.7K
Swift
Swift

7K
5K
+ 1
1.1K
- No public GitHub repository available -

What is Dart?

Dart is a cohesive, scalable platform for building apps that run on the web (where you can use Polymer) or on servers (such as with Google Cloud Platform). Use the Dart language, libraries, and tools to write anything from simple scripts to full-featured apps.

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 Swift?

Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.
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What are some alternatives to Dart, Go, and Swift?
TypeScript
TypeScript is a language for application-scale JavaScript development. It's a typed superset of JavaScript that compiles to plain JavaScript.
JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
Kotlin
Kotlin is a statically typed programming language for the JVM, Android and the browser, 100% interoperable with Java
PHP
Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.
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.
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Decisions about Dart, Go, and Swift
StackShare Editors
StackShare Editors
Rails
Rails
Node.js
Node.js
Python
Python
React
React
Java
Java
Ruby
Ruby
Go
Go
Swift
Swift
Objective-C
Objective-C
jQuery
jQuery

By mid-2015, around the time of the Series E, the Digital department at WeWork had grown to more than 40 people to support the company’s growing product needs.

By then, they’d migrated the main website off of WordPress to Ruby on Rails, and a combination React, Angular, and jQuery, though there were efforts to move entirely to React for the front-end.

The backend was structured around a microservices architecture built partially in Node.js, along with a combination of Ruby, Python, Bash, and Go. Swift/Objective-C and Java powered the mobile apps.

These technologies power the listings on the website, as well as various internal tools, like community manager dashboards as well as RFID hardware for access management.

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Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 24 upvotes · 2M views
atUber TechnologiesUber Technologies
Jaeger
Jaeger
Python
Python
Java
Java
Node.js
Node.js
Go
Go
C++
C++
Kubernetes
Kubernetes
JavaScript
JavaScript
Red Hat OpenShift
Red Hat OpenShift
C#
C#
Apache Spark
Apache Spark

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

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
Python
Python
Go
Go
Kubernetes
Kubernetes

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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StackShare Editors
StackShare Editors
Prometheus
Prometheus
Chef
Chef
Consul
Consul
Memcached
Memcached
Hack
Hack
Swift
Swift
Hadoop
Hadoop
Terraform
Terraform
Airflow
Airflow
Apache Spark
Apache Spark
Kubernetes
Kubernetes
gRPC
gRPC
HHVM (HipHop Virtual Machine)
HHVM (HipHop Virtual Machine)
Presto
Presto
Kotlin
Kotlin
Apache Thrift
Apache Thrift

Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.

Apps
  • Web: a mix of JavaScript/ES6 and React.
  • Desktop: And Electron to ship it as a desktop application.
  • Android: a mix of Java and Kotlin.
  • iOS: written in a mix of Objective C and Swift.
Backend
  • The core application and the API written in PHP/Hack that runs on HHVM.
  • The data is stored in MySQL using Vitess.
  • Caching is done using Memcached and MCRouter.
  • The search service takes help from SolrCloud, with various Java services.
  • The messaging system uses WebSockets with many services in Java and Go.
  • Load balancing is done using HAproxy with Consul for configuration.
  • Most services talk to each other over gRPC,
  • Some Thrift and JSON-over-HTTP
  • Voice and video calling service was built in Elixir.
Data warehouse
  • Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
Etc
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Visual Studio Code
Visual Studio Code
GitHub
GitHub
Linux
Linux
JavaScript
JavaScript
Swift
Swift
Java
Java
PHP
PHP
Python
Python
XML
XML
JSON
JSON
Git
Git
SVN (Subversion)
SVN (Subversion)

I use Visual Studio Code because at this time is a mature software and I can do practically everything using it.

  • It's free and open source: The project is hosted on GitHub and it’s free to download, fork, modify and contribute to the project.

  • Multi-platform: You can download binaries for different platforms, included Windows (x64), MacOS and Linux (.rpm and .deb packages)

  • LightWeight: It runs smoothly in different devices. It has an average memory and CPU usage. Starts almost immediately and it’s very stable.

  • Extended language support: Supports by default the majority of the most used languages and syntax like JavaScript, HTML, C#, Swift, Java, PHP, Python and others. Also, VS Code supports different file types associated to projects like .ini, .properties, XML and JSON files.

  • Integrated tools: Includes an integrated terminal, debugger, problem list and console output inspector. The project navigator sidebar is simple and powerful: you can manage your files and folders with ease. The command palette helps you find commands by text. The search widget has a powerful auto-complete feature to search and find your files.

  • Extensible and configurable: There are many extensions available for every language supported, including syntax highlighters, IntelliSense and code completion, and debuggers. There are also extension to manage application configuration and architecture like Docker and Jenkins.

  • Integrated with Git: You can visually manage your project repositories, pull, commit and push your changes, and easy conflict resolution.( there is support for SVN (Subversion) users by plugin)

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Michael Pfaff
Michael Pfaff
CEO & Developer at Pfaff Development · | 3 upvotes · 16.4K views
Dart
Dart
Java
Java

I use Dart because it is a fast, modern language with an intuitive package manager and syntax similar to Java, while less verbose (i.e. public by default, _ in front of a variable, class, etc. to be private). Dart has an excellent asynchronous syntax making asynchronous calls such as filesystem interaction or HTTP requests simple and concise.

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

Go is a high performance language with simple syntax / seman