If you’re modeling relational data, it doesn’t seem like you can get around using a DB that uses SQL, which to me is the worst: most programmers aren’t DB experts and the SQL they output is quite often terrible.
Not to dunk on the lemmy devs, they do a good job, but they themselves know that their SQL is bad. Luckily there are community members who stepped up and are doing a great job at fixing the numerous performance issues and tuning the DB settings, but not everybody has that kind of support, nor time.
Also, the translation step from binary (program) -> text (SQL) -> binary (server), just feels quite wrong. For HTML and CSS, it’s fine, but for SQL, where injection is still in the top 10 security risks, is there something better?
Yes, there are ORMs, but some languages don’t have them (rust has diesel for example, which still requires you to write SQL) and it would be great to “just” have a DB with a binary protocol that makes it unnecessary to write an ORM.
Does such a thing exist? Is there something better than SQL out there?
I’m absolutely biased as a data engineer who loves SQL, but there are some good reasons why SQL has been the de facto standard for interacting with databases since the 80s.
One of its draws is that it’s easy to understand. I can show a stakeholder that I’m selecting “sum(sale_amount) from transactions where date=yesterday” and they understand it. Many analysts are even able to write complicated queries when they don’t know anything else about programming.
Since it’s declarative, you rarely have to think about all the underlying fuckery that lets you query something like terabytes of data in redshift in minutes.
Debugging is often pretty nice too. I can take some query that didn’t do what it was supposed to and run it over and over in a console until the output is right.
I’m absolutely biased as a data engineer who loves SQL, but there are some good reasons why SQL has been the de facto standard for interacting with databases since the 80s.
I find it funny how the people who actually have to wrangle data swear by SQL as awesome, but there are always random hacks coming out of the woodwork, who don’t even look at SQL at all, with sweeping statements claiming SQL sucks because reasons.
It’s like the most opinionated people against SQL are the ones who don’t use SQL.
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I’m absolutely biased as a data engineer who loves SQL, but there are some good reasons why SQL has been the de facto standard for interacting with databases since the 80s.
One of its draws is that it’s easy to understand. I can show a stakeholder that I’m selecting “sum(sale_amount) from transactions where date=yesterday” and they understand it. Many analysts are even able to write complicated queries when they don’t know anything else about programming.
Since it’s declarative, you rarely have to think about all the underlying fuckery that lets you query something like terabytes of data in redshift in minutes.
Debugging is often pretty nice too. I can take some query that didn’t do what it was supposed to and run it over and over in a console until the output is right.
I find it funny how the people who actually have to wrangle data swear by SQL as awesome, but there are always random hacks coming out of the woodwork, who don’t even look at SQL at all, with sweeping statements claiming SQL sucks because reasons.
It’s like the most opinionated people against SQL are the ones who don’t use SQL.
it’s just a drag to veer from. it’s not particularly good, but good enough to stick around.