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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[–] kSPvhmTOlwvMd7Y7E@programming.dev 0 points 1 year ago (2 children)

and how you run your tests? Do you spawn a DB backend for test purposes?

[–] azezeB@discuss.tchncs.de 1 points 1 year ago

Yes, I create a dedicated dB in the test phase.

[–] MajorHavoc@lemmy.world 1 points 1 year ago* (last edited 1 year ago)

As another option in this case:

I've been able to write unit tests for SQL within the database to address testing important business logic that exists in SQL. The test fixtures just become stored (version controlled) database scripts to set needed test data in place in the test DB. Then we still mock over the db call in the code for unit tests as usual.

It's more effort up front, but I find it much easier to maintain complex DB interactions inside the DB, isolated from the downstream consumer code.

Obviously, there's an art to knowing when this is needed, or appropriate. I've worked for organizations where almost everything important was a performant SQL query. In that org, maintenance got dramatically simpler and the product more reliable when we started writing SQL tests after moving important DB work directly into the DB.