this post was submitted on 08 Sep 2023
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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.

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[–] [email protected] 1 points 1 year ago* (last edited 1 year ago)

Yeah, I have my own stuff that lets me do MSSQL, DynamoDB, REST/HATEAOS, regular Hash Maps, and some obscure databases (FilePro).

I throw them in a tree structure and perform depth-first searches for resources. Some of them have stuff for change data capture streaming as well, (eg: SQLNotifications, DynamoDB Stream, WebSockets).

DynamoDB was a rough one to optimize because I have to code to pick the best index. You don't do that with SQL.

The code on backend is the same as frontend, but a different tree. Frontend queries against REST and a cache layer. Backend queries against anything, REST included.