My name is Ryan and I'm a coder. Hence matrixguy.com. After doing freelance work for a while, I decided to create a Google doc to briefly recap various technologies because, well, there can be so many to remember. I've decided to make this information available for others to benefit from, which will be updated from time to time. Enjoy!

Table of Contents

Amazon Elastic Transcoder

Apollo

apt-get

Bare Metal Server

BEM

Bootstrap

Browsersync

Bug-tracking services

Closure

Cloud Speech API

Composer

CORS

CSS

SASS

Tailwind

Docker

Elastic Beanstalk

ES6 / ES2015

Firebase

Frontend frameworks

git

Go

Google Tag Manager

GraphQL

Hadoop

HAProxy

Haskell

Headless browser

Heroku

HTML5

HTTP request methods

Hypervisor server

Idempotence

Javascript frameworks

Alpine.js

Angular

React

VueJS

Load balancing

Other JS libraries/frameworks

Babel

Bower

Webpack

TypeScript

JSON API

JWT

Kubernetes / K8S

Lisp

Machine learning

Maven

MongoDB

NFS/SMB

Node.js

NoSQL

npm/yarn

npm packages

grunt

gulp

Progressive Web App

React Native

RDS

Redis

REST

S3

Scala

Serverless Architecture

AWS Lambda

Google Cloud Platform

IBM Cloud Functions

Microsoft Azure

Software tools

InVision

Zapier

SQL JOINS

Television screens

Terms

UDP vs TCP

Vagrant

Video tech

Webkit

Web RTC

WebAssembly

Websockets

WebUSB

Wireless antenna

Wireless standards

Amazon Elastic Transcoder

Apollo

apt-get

Bare Metal Server

BEM

Bootstrap

Browsersync

Bug-tracking services

Closure

Cloud Speech API

Composer

CORS

CSS

SASS

Tailwind

Docker

Elastic Beanstalk

ES6 / ES2015

function(task) {

        return console.log(‘foo’);

}

(task) => {

         console.log(‘foo’); [b]

}

task [c]  => {

        console.log(‘foo’);

}

task => console.log(‘foo’)

Firebase

Frontend frameworks

Learning curve: Vue > React > Angular

Popularity: React > Angular > Vue

git

Go

Google Tag Manager

GraphQL

Hadoop

HAProxy

Haskell

Headless browser

Heroku

HTML5

HTTP request methods

Hypervisor server

Idempotence

Javascript frameworks

Alpine.js

Angular

React

VueJS

Load balancing

DNS

Hardware

Software

Other JS libraries/frameworks

mounted() {

        axios.get(‘/skills’).then(response => this.skills = response.data);

}

Babel

Bower

Webpack

TypeScript

JSON API

JWT

Kubernetes / K8S

Lisp

Machine learning

Maven

MongoDB

add field

db.actors.update({}, {

$set: { "approved": true }

}, { upsert: false, multi: true })

rename field

        db.actors.updateMany({}, {

                $rename: { “resume_url”: “resume” }

        })

NFS/SMB

Node.js

NoSQL

Quite simply, doesn’t use SQL. But generally they are non-relational, of which there are three categories:

  1. Document model : Stores data in documents such as JSON, eliminating the need for joins. Also, each document can contain different fields.
  1. Examples : MongoDB, CouchDB
  2. Consistency : MongoDB provides tunable consistency. By default, data is consistent — all writes and reads access the primary copy of the data. As an option, read queries can be issued against secondary copies where data maybe eventually consistent if the write operation has not yet been synchronized with the secondary copy; the consistency choice is made at the query level.
  3. Visualization and Reporting : Many companies conduct data visualization, analytics, and reporting using SQL-based BI platforms that do not natively integrate with NoSQL technologies. To address this, organizations turn to OBDC drivers that provide industry-standard connectivity between their NoSQL databases and 3rd party analytics tools. For example, the MongoDB Connector for BI allows analysts, data scientists, and business users to seamlessly visualize semi-structured and unstructured data managed in MongoDB, alongside traditional data from their SQL databases, using the most popular BI tools.
  1. Graph model :  Data is modeled as a network of relationships between specific elements. While the graph model may be counter-intuitive and takes some time to understand, it can be useful for a specific class of queries. Its main appeal is that it makes it easier to model and navigate relationships between entities in an application. Graph databases are useful in cases where traversing relationships are core to the application, like navigating social network connections, network topologies or supply chains.
  1. Examples : Neo4j, Giraph
  1. Key-Value model : Most basic type of non-relational database. Every item in the database is stored as an attribute name, or key, together with its value. The value, however, is entirely opaque to the system; data can only be queried by the key. Key value stores and wide column stores are useful for a narrow set of applications that only query data by a single key value. The appeal of these systems is their performance and scalability, which can be highly optimized due to the simplicity of the data access patterns and opacity of the data itself.
  1. Examples : Riak, Redis

npm/yarn

npm packages

Progressive Web App

React Native

RDS

Redis

REST

S3

Scala

A general-purpose programming language providing support for functional programming and a strong static type system. Designed to be concise,[10] many of Scala's design decisions aimed to address criticisms of Java

Serverless Architecture

AWS Lambda

Google Cloud Platform

IBM Cloud Functions

Microsoft Azure

Software tools

InVision

Zapier

SQL JOINS

Television screens

Terms

UDP vs TCP

Vagrant

Video tech

Webkit

Web RTC

WebAssembly

Websockets

WebUSB

Wireless antenna

   

Wireless standards

[a] Take up the screen

[b] 'return' is implicit.

[c] Only works for a single argument. If no arguments, can use () =>

[d] Can also be a function itself.

[e] Maybe not anymore?