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Relative to the alternatives, I love it.
I wrote a relational database from scratch in college for one of my classes (its the only assignment we were given). I get them. They're like a crazy best friend - crazy on the outside, deeply sane on the inside, irreplaceable.
There's a half century of research invested into them. Normal data is so so so so underestimated. (At least in applications like this.)
Fair. I don't even really know what the alternatives are.
My background doesn't deal much with live data, so I'm mostly happy using pandas in python, but no one uses that for a production database.
I'm sure someone uses a pandas franken-db in prod. I read a book about using ElasticSearch as a production DB.
I think my beef with SQL is that wherever I've seen it used, complex queries are often written out entirely in a single chunk of code. Not sure if the language doesn't lend itself well to modularity, but these chunky queries always seemed hard to decipher and thus error prone.
That's a great point. I took the lack of composability for granted. I'm sure there are awesome alternatives aimed at fixing that.
Why change the language if you can just use a query builder? I really liked Knex at my previous job.
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I wonder if you hate working with SQL as much as I do