Build Performant GraphQL Backends in Days using Hasura

Transform your database into a GraphQL server with built-in sorting, full-text search, and pagination in a few minutes
Use a simple file uploading strategy with GraphQL, Hasura actions, and Firebase storage
Build a D pipeline with GitHub Actions that deploys the Hasura project on development and production environments
Use a simple file uploading strategy with GraphQL, Hasura Actions, and Firebase storage
Easily integrate and delegate custom logic to micro-services (REST and GraphQL) created with Firebase Cloud functions
Database migrations and metadata to help your database evolve successfully
Create role-based access to the data
Create full React and Angular application examples with Apollo GraphQL client and Hasura backend
Build real- queries to the Hasura GraphQL server
If you're a developer struggling with GraphQL because of its complexity or simply because it takes too much , this is going to be the most exciting news for you.
If you get to know that your existing PostgreSQL (and soon MySQL too) can be turned into a powerful GraphQL API in a matter of seconds or build a performant GraphQL backend from start to finish in a couple of hours with very little to no coding-would you be interested
This course provides you with a solution. This course will talk about "Hasura", which will help you create your GraphQL backends easier and faster than you ever thought possible without writing a single line of code!
Here, you will look at how to let the CRUD code write itself without you even touching your keyboard. Then you'll learn how to play with all the different features in Hasura using the "playground" approach. After that, you'll understand how to easily navigate through the most common errors that can cost you a huge chunk of your if you don't know about them. Finally, you'll use Angular and React apps to enhance Hasura features and deploy the code on GitHub Actions.
By the end of this course, you'll be able to use every functionality to create your GraphQL backends effortlessly in record .
The resource files are uploaded on the GitHub repository at






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