reshape VS ent

Cool stuff! Do you have any thoughts about how this compares to https://github.com/fabianlindfors/reshape?

From what I know, there is only one project that tries something close to this: the relatively recent Reshape. It uses Postgres views to expose the two versions of the schema and triggers to upgrade/downgrade the new data. It doesn’t do the constraints part as described above, but shows that this approach is possible. Combined with the Xata pull request based workflow, I think the ideal system described above is possible!

My idea is not unique. Reshape is similar, but bigger in scope.

This is precisely what I did for my automated zero-downtime migration tool and it works pretty well: https://github.com/fabianlindfors/reshape. At least for Postgres, simple views like these have almost no overhead as queries are simply rewritten for the underlying table.

Anybody interested in this subject might also be interested in a tool for Postgres I’ve been working on, Reshape: https://github.com/fabianlindfors/reshape. It aims to fully automate away all the pain and manual steps zero-downtime migrations normally requires :)

This post is absolutely terrific and has been been my main reference for Reshape, an automated, zero-downtime schema migration tool: https://github.com/fabianlindfors/reshape

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