goose VS ent

In v3.16.0 we added a new Provider feature that unlocks the ability to implement a lot of highly requested features. More details in the blog post:

Next try https://github.com/pressly/goose We have this setup to be run by the CI-CD pipeline to be run before the application is started. BTW, this utility is compatible with https://sqlc.dev , so they work good together.

For database migration I recommend https://github.com/pressly/goose As it works with sqlc and is a powerful tool for complex migrations. This is something a lot of ORMs are really weak with. I was on a large project with Gorm as the ORM and what a nightmare when we pushed to production!

goose https://github.com/pressly/goose - data migration and seed data creation

I'm using .sql migration files with tooling similar to https://github.com/pressly/goose . Is there a way to manage my schema with my pre-existing tooling and my queries/CRUD operations with Ent/Atlas?

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