SQLBoiler VS GORM

SQLBoiler takes a database-first approach, generating Go code from your database schema. This means it creates highly optimized and custom-tailored code for your specific database schema. SQLBoiler is great for applications where the database schema is well-defined and changes infrequently. However, like sqlc, it requires regenerating the code when the database schema changes. It's well-suited for projects where performance is a key concern and the database design is stable​.

Moved all my projects to https://github.com/volatiletech/sqlboiler.

sqlboiler

My current ORM of choice is Bob [GitHub Link] which I created based on my experience using and maintaining SQLBoiler [GitHub Link].

You mean like ORMs? * sqlboiler: generates Go ORM using database schema.

SQL code generator (aka inspect a database or SQL files to generate data models). You have the option of using something like volatiletech/sqlboiler which looks at the a physical database and generates code based on the schema. Or SQLC which is an amazing and fast project.

After trying a half dozen migration engines for NodeJS, I was pleased to see Prisma and its excellent documentation. As a golang developer I am partial to SQLBoiler and its database-first approach, though perhaps this is a condition of our community where we want all the knobs. Prisma was code-first but still gave me enough control to feel confident.

I use sqlboiler which generates an ORM from your database, and sql-migrate which is a tool for managing SQL migrations. Although you have to write your migrations in SQL, which IMHO is a plus.

FWIW, the other posts point to https://gobuffalo.io/ and https://github.com/volatiletech/sqlboiler as possibilities.

GORM is a comprehensive ORM tool in Go, offering a code-first approach which allows defining database schemas using struct tags in Go. It's known for its developer-friendly nature, making it suitable for both beginners and experienced users. GORM supports a variety of SQL databases like MySQL, PostgreSQL, and SQLite. It's designed to be flexible, allowing developers to drop down to raw SQL when necessary. However, it's important to be cautious about its performance implications in large-scale applications.

Homepage: https://gorm.io/

Since most of these APIs will be simple CRUD (Create/Read/Update/Delete) endpoints, let's build this service using GORM, an ORM library that makes building CRUD endpoints really simple.

After successfully configuring the application, it's time to delve into integrating the data layer. For this purpose, I will utilize gorm, a powerful SQL ORM that facilitates rapid development of the data layer using model structs.

For basic INSERT ... VALUES ... or SELECT ... WHERE ... JOIN ..., use a library such as GORM. For INSERT .... SELECT ... statements where one combines two round trips (SELECT and INSERT) into one, ORMs have a hard time performing this query. Particularly when you start doing joins. Joins are the heart of Relational database theory (they denote relationships). So get to know what an INNER, LEFT, RIGHT and OUTER join is and why you would use them. Also learn INSERT ... SELECT ...

I have never hated gorm and it serves me well. However I tend to feed it raw SQL very often.

Array of values with embedded value all pointed to the last value, reflect code was broken: https://github.com/go-gorm/gorm/pull/5901 data corruption