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] 4 points 1 year ago

TL;DR you can't be an expert at every aspect of coding, so I let the big boys handle SQL and don't torture the world with my abysmal SQL code.

I've seen enough bad SQL to claim you're wrong (I write bad SQL myself, so if you write SQL like I do, you're bad at it).

Seriously, the large majority of devs write terrible SQL and don't know how to optimise queries in any way. They just mash together a query with whichever JOIN they learned first. NATURAL JOIN? Sure, don't mind if I do! Might end up being a LEFT JOIN, RIGHT JOIN, or INNER JOIN, but at least I got my data back right? Off the top of your head, do you know all the joins that exist, when to use which one, and which ones are aliases for another? Do you know how to write optimal JOINs when querying data with multiple relations?

When writing similar queries, do you think most are going to copy-paste something that worked and adapt it? What if you find out that it could be optimised? Then you'll have to search for all queries that look somewhat similar and fix those.

When you create an index for a table, are you going to tell me you are going to read up on the different types each time to make sure you're using the one that makes sense? Postgres has 6, MySQL only has 2 tbf depending on storage engine, but what about other DBs? If you write something for one DB and a client or user wants to host it with another, what will your code look like afterwards?

Others have brought up models in code, so that's already discussed, but what about migrations? Do you think it's time well-spent writing every single migration yourself? I had the distinct pleasure of having to deal with hand-written migrations that were copy-pasted and modified columns that had nothing to do with the changed models, weren't in a transaction, failed half-way through, and tracking down which migration had actually failed. These were seasoned developers who completely forgot to put any migration in transactions. They had to learn the hard way.