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Airtable’s core stack is written using JavaScript, and augmented with static type checking and other tools. We use Node.js on the backend, and mostly React on the front end, but our application requirements drive a substantial amount of custom software architecture; that is, Airtable is pretty far from a boilerplate “React + Express” application. Mobile apps are currently native and use JavaScript in webviews where appropriate. Our data infrastructure, which drives our data science and business intelligence efforts, is primarily in Python. We periodically evaluate adding other languages into our codebase for ecosystem or performance reasons; philosophically, we try hard to standardize on a few languages and toolchains so that investments in tooling can be leveraged across larger fractions of our engineering effort. Our production infrastructure runs on a variety of AWS services, principally using Terraform for deployment; for logging, aggregation, monitoring, and alerting, we use a mixture of ELK and some carefully selected third-party services.

Python, JavaScript, Ruby, Unix, Linux, React.js, Ruby-on-Rails, Ajax, Docker, SQL, Apache, Amazon-web-services, DataDog

Swift, JavaScript, TypeScript, Native iOS, UIKit, Combine, Node.js, Vapor Swift, React, Next.js, Postgres, MongoDB

Javascript, Meteor, Semantic UI, Docker, Kubernetes, MongoDB, AWS

Full stack Javascript, Typescript, Node, React, Redux, Apollo, GraphQL, Redis, MongoDB, Elasticsearch, AWS (Codepipeline, ECR, ECS, Fargate) and serverless (Lambda, SQS, SNS).