graphql-voyager VS ent

Disclosure of the schema of a GraphQL API is at least informational. You can use a tool such as GraphQL Voyager to visualize what you got and see if there are any unprotected sensitive operations available.

Very cool! We had been using various tools like [graphqlviz](https://github.com/sheerun/graphqlviz) [graphql-voyager](https://apis.guru/graphql-voyager/) but past a certain level of complexity they tended to be not great. I'm going to try this out on some pretty gnarly tables and see how it does!

Introspection is typically used by the tooling to understand your GraphQL types and schema. For instance, tools like GraphQL Voyager can introspect your schema and build amazing graphs, and almost all extensions built around GraphQL leverage this power to understand your schema, types and everything around it.

https://github.com/APIs-guru/graphql-voyager allows you to visualize the schema

Voyager

https://apis.guru/graphql-voyager/ you can visualize your schema as a graph

Also https://github.com/APIs-guru/graphql-voyager.

For data visualisation I think Voyager does an excellent job.

Yep, it does. But I didn't code it, it's an open source client that I just embedded within the plugin: https://github.com/APIs-guru/graphql-voyager

In this article, we'll delve into the world of concurrency control in Go, specifically focusing on the optimistic locking approach. We'll explore its implementation using Ent ORM to illustrate how to manage data consistency when multiple users interact with the same resource. Keep in mind that this example serves as a simplified illustration, and real-world booking systems involve a many of additional complexities. However, the core concepts presented here provide a solid foundation for understanding optimistic locking in Go applications. Feel free to explore the complete source code in my GitHub repository for a more in-depth look at the implementation.

ent is a fairly recent ORM that uses a code-first approach where you define your schema in Go code. Ent is popular thanks to its ability to handle complex data models and relationships elegantly. It's statically typed, which can help catch errors at compile time. However, the learning curve might be steeper compared to more straightforward ORMs like GORM. It's a good fit for applications where complex data models and type safety are priorities.

If you found this article, than you are probably similar to how I was a few months ago. I started a project in Go that required a SQL backend and I wanted to use any tool that would help me build this backend quickly. I stumbled upon entgo (an ORM for Go) and decided to give it a try.

The ent orm for golang actually does some useful work for you. https://github.com/ent/ent

Backend Database interaction with entgo

You can use entgo.io for ORM stuff, it also has entgql extension that integrated with GQLGen. See more at the document: https://entgo.io/docs/tutorial-todo-gql