graphjin VS ent

This one looks interesting if you like GraphQL… https://graphjin.com

You're right. Django made a ton of tables, and it's pretty insightful to think about all the stuff it's trying to consider and a nightmare to migrate that framework. Django might have simplified some stuff, but it's still too opaque for my taste and the overall end goals of the project. Currently, I'm testing using graphjin (it doesn't have the best documentation, but it does boast an SQL generation capability that I philosophically think is the best way to do things).

Checkout GraphJin it's an automatic GraphQL to SQL compiler, you write your database queries in GraphQL instead of SQL and it compiles them into efficient SQL on the fly. Works as a library in GO and NodeJS. https://github.com/dosco/graphjin

In GraphJin an automatic GraphQL to SQL compiler we use the gnomock library it startups a database instance (docker) then create the schema and tests data and finally our code connects to it and runs a series of tests. We run these across Mysql, Postgres and a few other DB's. Gnomock supports a wide range of them. Right now we don't take down the db for every test only between test runs but its fast enough that we could. This whole thing runs of a simple `go test -v .` command and we run it on every commit using a githook. https://github.com/dosco/graphjin/blob/master/tests/dbint_te...

This was a bug in GraphJin it has since been fixed. The issue was that you were trying to have multiple subscriptions over a single websocket this did not work (it should) and now it does. https://github.com/dosco/graphjin/commit/43e619b2ff392dd42b99a4d56074a041a54b0e1c

Not exactly GraphQL is just a format to define what data you want back from someplace. You can use it in a browser app to request data from a backend GraphQL server or you can use it as an ORM within your backend app to fetch data from a database using a library like GraphJin. https://github.com/dosco/graphjin

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