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AWS, Python, GoLang, Cloud9, GitHub, ELK, Cloudera

Backend: NodeJS, Go, Ruby on Rails. DB: Postgres, MySQL, Redis. Frontend: React, Redux, Webpack. APIS: GraphQL, GCloud PubSub. Google Cloud Platform. Docker, Kubernetes.

Web stack: Django, GraphQL, React, Postgres. Data pipeline: Spark, Kafka, Elastic Search, Scala. Infra: AWS.

Backend: Ruby on Rails, Postgres, Elasticsearch, Google Cloud Platform, Kubernetes

Frontend: Typescript, React, Redux

Data: BigQuery, BigTable, DataFlow, DataProc

Airtable’s core stack is written using JavaScript, augmented with static type checking and other tools. We use Node.js on the backend, and mostly-React on the frontend, but our application requirements drive a substantial amount of custom software architecture; that is, Airtable is pretty far from a boilerplate “React + Express” application. We also periodically evaluate adding other languages into our codebase for ecosystem or performance reasons. Mobile apps are currently written in the standard platform language, mixed with JavaScript in webviews where appropriate. Our production infrastructure runs on a variety of AWS services, principally using Terraform for deployment; for data collection, aggregation, monitoring, and alerting, we use a mixture of ELK and some carefully selected third-party services.

Across our product portfolio we leverage a variety of languages, frameworks and tooling. Much of our code is written in C#/.NET Core 2.x along with a handful of other languages such as C++, PHP, Node.js and Java. For frontend, Angular 6+ on the newer products, and a few mature products leveraging Javascript and JQuery. Many databases to store our 300TB+ of production data including MySQL, SQL Server, MongoDB, Snowflake, DynamoDB & RDS. We have some monolithic applications though new products & platforms are built using microservices running Docker containers on AWS ECS with some footprint in Azure. We leverage many AWS services – Lambda, CloudWatch, S3, EC2, Route53, IAM, SQS, SNS and more. We also use Terraform for configuring infrastructure, Jenkins for CI, and Git/GitLab for source code. These are flexible (they can and will change) and what a candidate knows for stack is not as important as their ability to think creatively – we can train languages, it’s much harder to train curiosity and intellectual drive.

Ruby, Rails, Javascript, React, MySQL, Kubernetes

Ruby on Rails

Swift

Postgres

Redis

Memcache

RabbitMQ

AWS

Heroku

Ruby / Javascript / Python / Golang

Sinatra / Rails / React

MySQL / Mongo

Presto for data warehouse

Docker / Kubernetes for deployment

REST / JSON / gRPC for service communication

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).

React, Redux, Node, Java, Postgres, 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).

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