50 lines
2.1 KiB
Markdown
50 lines
2.1 KiB
Markdown
# Technical Stack
|
|
|
|
## Airbyte Core Backend
|
|
|
|
- [Java 21](https://jdk.java.net/archive/)
|
|
- Framework: [Micronaut](https://micronaut.io/)
|
|
- API: [OAS3](https://www.openapis.org/)
|
|
- Databases: [PostgreSQL](https://www.postgresql.org/)
|
|
- Unit & E2E testing: [JUnit 5](https://junit.org/junit5)
|
|
- Orchestration: [Temporal](https://temporal.io)
|
|
|
|
## Connectors
|
|
|
|
Connectors can be written in any language. However the most common languages are:
|
|
|
|
- Python 3.9 or higher
|
|
- [Java 21](https://jdk.java.net/archive/)
|
|
|
|
## **Frontend**
|
|
|
|
- [Node.js](https://nodejs.org/en/)
|
|
- [TypeScript](https://www.typescriptlang.org/)
|
|
- Web Framework/Library: [React](https://reactjs.org/)
|
|
|
|
## Additional Tools
|
|
|
|
- CI/CD: [GitHub Actions](https://github.com/features/actions)
|
|
- Containerization: [Docker](https://www.docker.com/) and [Docker Compose](https://docs.docker.com/compose/)
|
|
- Linter \(Frontend\): [ESLint](https://eslint.org/)
|
|
- Formatter \(Frontend & Backend\): [Prettier](https://prettier.io/)
|
|
- Formatter \(Backend\): [Spotless](https://github.com/diffplug/spotless)
|
|
|
|
## FAQ
|
|
|
|
### _Why do we write most destination/database connectors in Java?_
|
|
|
|
JDBC makes writing reusable database connector frameworks fairly easy, saving us a lot of development time.
|
|
|
|
### _Why are most REST API connectors written in Python?_
|
|
|
|
Most contributors felt comfortable writing in Python, so we created a [Python CDK](../connector-development/cdk-python/) to accelerate this development. You can write a connector from scratch in any language as long as it follows the [Airbyte Specification](airbyte-protocol.md).
|
|
|
|
### _Why did we choose to build the server with Java?_
|
|
|
|
Simply put, the team has more experience writing production Java code.
|
|
|
|
### _Why do we use_ [_Temporal_](https://temporal.io) _for orchestration?_
|
|
|
|
Temporal solves the two major hurdles that exist in orchestrating hundreds to thousands of jobs simultaneously: scaling state management and proper queue management. Temporal solves this by offering primitives that allow serialising the jobs' current runtime memory into a DB. Since a job's entire state is stored, it's trivial to recover from failures, and it's easy to determine if a job was assigned correctly.
|