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Python, Flask, PostgreSQL, Redis, Heroku, AWS, GraphQL, React Native

Outside of our data teams, our engineering teams use Java, JBoss, CDI/Spring, Freemarker, Jquery, Knockout, SpringBoot, Redis Kinesis, Docker.

Our Data Engineering team uses Groovy, Redshift, AWS Data Pipeline, AWS Lambda, Cassandra, AWS Elastic Bean Stalk, Python, Docker.

Our Data Science team uses Python, Jupyter Notebook, SciKitLearn, Redshift, and Docker.

Cloud Foundry on AWS for hosting all servers, Akamai CDN, Java 8/Kotlin used on all backend services and APIs, RDS (AWS MySQL) used for account data storage, AWS S3 used for raw storage, RedShift used for analytics, React.js used for web based front end clients (including dashboards), Swift for iOS, Kotlin for Android, Python for Data Science

Python, Javascript, React, GraphQL, PostgreSQL, Chrome extensions

Our engineering team builds software using JavaScript/ES6, React, Redux, Swift, and Objective-C on the frontend and Python, bash, and Bitcoin Core on the backend.

Frontend: React, Relay, Flow, Jest, Enzyme

Mobile: React Native, Apollo

Backend: Ruby on Rails, Postgres, GraphQL, Python, RSpec

CI: GitHub, Buildkite

Infrastructure: AWS, Python

Web - Node, React, Python, PostgreSQL

Mobile - React Native, Swift (iOS) / Java (Android)

Python

MySQL

Redis

Kinesis

HAProxy

Linux

Javascript

React

Redux

Flux

Flow

Elasticsearch

AWS

Jenkins

MyPy

nginx

We have a service oriented stack deployed on AWS using containers. Most of our backend services are written in Go, with the exception of an NLP/ML service written in Python. Services talk to each other using gRPC.

Our web application is served statically from Cloudfront/S3 and is written using React. Is is a Progressive Web App, with a service worker to speed up delivery.

We integrate with third party software such as Google Drive, Calendar, Jira, GitHub, Asana, Slack. These areas are some of the most complex parts of our systems. They’re also some of the most important: integrations enable the “magic” of a user coming to Range in the morning and seeing all of their work from the previous day already gathered in one place.

Some of the technologies we use to build Thread include: Python, Django, ReactJS, PostgreSQL, Redis, Debian, Docker, Memcache, nginx, Ansible, Jenkins, Gunicorn, Luigi, Pandas, scikit-learn, git.

React/Redux, Android (native, Kotlin), Python (using Flask / SQLAlchemy), Postgresql, AWS

Some popular languages and frameworks we use are: (Web) JavaScript, Python, Go, Java, PHP, Ruby | Node.js, Express, Spring, ReactJS, Redux, Typescript, Rails. (Android) Kotlin, Java | RxJava, React Native. (iOS) Swift, Objective-C | RxSwift, React Native

Ruby on Rails, React, Redux, React Native, Sass, Redis, ElasticSearch, Postgres, Heroku, Airflow, Python 3

Python, Django, Postgres, Objective-C, Swift, PyTorch

Python (Flask)

ReactJS / Redux

MongoDB

Ruby / Javascript / Python / Golang

Sinatra / Rails / React

MySQL / Mongo

Presto for data warehouse

Docker / Kubernetes for deployment

REST / JSON / gRPC for service communication

Engineering: Ruby on Rails, React, Postgresql, ElasticSearch

Data: Python + Go, Docker, AWS services (e.g. Kinesis, Lambda, ECS, Fargate…)

Frontend: Javascript, React, Typescript, Flow, Mobx, Stylus, Redux, Reactive JS, Styled Components, Focal (our own in-house, open-sourced state management framework)

Mobile (iOS and Android): Java, OkHttp, Butterknife, Retrofit, XCode, Swift, ReactiveCocoa, ReactiveSwift, Kickstarter-Prelude, Argo, Runes, Curry

Desktop app: CoffeeScript, Electron.js, C#, F#, ReactiveUI

Internal tools: Angular, Elm, ClojureScript

Backend: Java, Scala, Python, Haskell, Lisp, Clojure, Go, C++

NLP/Research teams: sklearn, TensorFlow, PyTorch, CNN, RNN, Keras, Seq2Seq, xgboost, CRFs, nltk/spacy/OpenNLP, OpenNMT, Jupyter notebooks

Single source multi-tenant AWS SaaS offering

Leveraging many AWS services (Lambda, Kinesis, Redshift, etc.)

Backend - Clojure / Java / Node.JS / Python

Frontend - Angular

DB - Couchbase / Postgres / Redshift

Rails for user facing side

React

Python for backend integrations/data science

TypeScript, JavaScript, and React

Scala (high performance backend)

Python (infrastructure management and data analysis)

Android and iOS

Luna1 (legacy in-house functional reactive framework, similar to Meteor)

Frontend: React/Redux. Legacy JSP (although increasingly less!)

Monolith backend: Java on Tomcat.

Microservices backend: Java on Spring.

API: Java w/ Swagger.

TechOps: Hashicorp stack + Docker on EC2/AWS. Cloudflare, EBS, Redis. Git/GitHub for Source Control. Jenkins for CI. Ruby/Cucumber for testing.

Databases: MySQL

Search: SOLR

Data: Python (pandas, AirFlow, etc.). Redshift/Postgres.

OnForce Platform (subsidiary): PHP on baremetal LAMP (deprecating, moving to AWS).

Our main app is a Ruby on Rails API, with a Postgres and PostGIS database and a front-end built using React.js. It’s hosted in Heroku. We also have a variety of services built in Python that are hosted on AWS.

We’re primarily a Python shop, using Django for our websites. We also have a few services written in Go and have started to build out our front ends using React. We use Github to host our code, Jenkins (for now) to automate our tests, and right now most of our applications and code live in VMs in a Colo just outside of Toronto. We’re in the process of transitioning to AWS. Other common technologies we use are Postgres (primary DBs), Redis (cache and key/value store), RabbitMQ (messaging broker) and Celery (task queue).

JavaScript/CoffeeScript, Python, Node.js, React + React Native, AWS Lambda, Spark, Kinesis, MongoDB, Redshift

Python / Django Scala Golang Postgres Cassandra ElasticSearch Redis AWS (EC2, S3, ALB, EBS, Kinesis, SQS) Linux (Ubuntu)

Tech stack varies from team to team: PHP, React, Java, Node, Scala, Objective-C, Go, etc.

AWS rds + mysql for data storage API is in python + flask apache thrift for interface definition android app is in java ios apps in swift 3 front-end web is in python, flask, node, and react

Ruby on Rails, Java, Python, Haskell, Postgres, Redis, AWS, Docker