Typed-GraphQL Performance Optimization
While working on a project for a client, we came across an interesting twist to a common problem. We were tasked with making the API backend that powers a mobile app called Playhouse, a mobile app that displays real estate listings to its users in a nice little video package. We decided to make a GraphQL API and got to building. During the design process, we made a point of keeping it maintainable for the long run.
Part 2 - Persisting Data To Database
This is article is part of a series. They are: Part 1 - Simple GraphQL Server with Juniper And Actix Part 2 - Persisting Data To Database In the previous blog post, we showed how easy it is to create a GraphQL server in Rust. In this post, we will hook it up to a Postgres database. To do this we will use the tokio-postgres package. While it is possible to use an ORM in Rust (the most popular choice being diesel), that topic is very dense on its own, and even in high level frameworks like Node.
Part 1 - Simple GraphQL Server with Juniper And Actix
This is article is part of a series. They are: Part 1 - Simple GraphQL Server with Juniper And Actix Part 2 - Persisting Data To Database Rust is an upcoming programming language that is often regarded as a low-level systems language, however it comes with language features that allow it to extend itself into other domains while minimizing the boilerplate you might expect from a systems language. We will be looking at Rust as a GraphQL Server and demonstrating its simplicity when paired with powerful frameworks such as Juniper and Actix Web.