Some backend libraries let you write SQL queries as they are and deliver them to the database. They still handle making the connection, pooling, etc.

ORMs introduce a different API for making SQL queries, with the aim to make it easier. But I find them always subpar to SQL, and often times they miss advanced features (and sometimes not even those advanced).

It also means every time I use a ORM, I have to learn this ORM’s API.

SQL is already a high level language abstracting inner workings of the database. So I find the promise of ease of use not to beat SQL. And I don’t like abstracting an already high level abstraction.

Alright, I admit, there are a few advantages:

  • if I don’t know SQL and don’t plan on learning it, it is easier to learn a ORM
  • if I want better out of the box syntax highlighting (as SQL queries may be interpreted as pure strings)
  • if I want to use structures similar to my programming language (classes, functions, etc).

But ultimately I find these benefits far outweighed by the benefits of pure sql.

  • @asyncrosaurus
    6•10 months ago

    I find ORMs exist best in a mid-sized project, most valuable in a CQRS context.

    For anything small, they massively over complicate the architecture. For the large enterprise systems, they always seem to choke on an already large and complex domain.

    So a mid size project, maybe with less than a hundred or so data objects works best with an ORM. In that way, they’ve also been most productive mainly for the CUD of the CRUD approach. I’d rather write my domain logic with the speed and safety of an ORM during writes, but leverage the flexibility and expressiveness of SQL when I’m crafting efficient read queries.