GORM VS ent

GORM is an ORM (Object-Relational Mapping) library that simplifies database operations. It supports SQLite, PostgreSQL, MySQL, and more, with features like migrations, associations, and query building.

2. GORM

Go doesn't support migrations natively for that propuso we can use the popular golang-migrate package also if you use an ORM like GORM you can use it for that.

I never understood why people are so stubborn about hating on orm.

For example I'm familiar with https://gorm.io and it does save me a lot of time and useless boilerplate.

And guess what, if I ever need to make a complex query, I also happen to know SQL, and I'm just going to make a "raw" query https://gorm.io/docs/sql_builder.html#Raw-SQL and be done with it.

It's not all that hard.

SQL database: PostgreSQL Object Relation Mapping using Gorm

The previous post demonstrated receiving the raw data and unmarshalling it into a struct that was already annotated with gorm tags. Gorm is a popular ORM for Go. If you are not familiar with it, you can for more information here.

GORM is a, quite conveniently named, ORM for GO

Written in GIN framework and uses GORM as ORM.

There are ORMs like gorm that supports some kind of documentation with files, but they mainly focus on converting the database to "things" in the code to be used by the ORM, and not as documentation only/documentation-first.

> Ent heavily uses joins

I’m specifically talking about this: https://github.com/ent/ent/issues/977.

Devs assume that the `With` methods are adding join clauses but that is not typically the case.

> does support multi field indices

Composite primary keys are useful for reasons other than unique constraints and query speed. For example, CockroachDB uses the primary key to partition rows. Also, at scale, an extra multi-column index in addition to the primary key when the primary key alone could have sufficed can be a meaningful performance degradation.

> not a Graph DB under the hood

No it is not, but because it has a graph ‘mindset’ and does support Gremlin, traditional SQL folks expecting a lightweight ORM (such as Drizzle in the JS world) may not have a good time.

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