That particular post ends with a wish-list of items so it's the most similar to the OP. But there are others on the site that I quite enjoy (click on the home icon and search "SQL" on the page).
My personal take is that SQL will continue to reign for a long time because of the how monumental the task of replacing it is due to the inherent complexity of databases. LLMs make this worse because they're really good at translating prose to SQL. Now that it matters less how annoying SQL is to programmers, SQL will become more like assembly over time: something mostly computers write because it's complicated for humans to deal with directly. This is deeply ironic given that SQL was ostensibly designed to read like prose, i.e. to be easy for humans.
As a meta comment, I can handle code blocks without syntax highlighting, and I can handle code blocks that wrap. But both together with long comments just turn into line noise. There's no longer any useful visual signal for how to read them. On my phone the code blocks are simply impossible to meaningfully parse.
This would have been interesting about a decade ago, but today AIs all know SQL, and I haven't written it myself in a while.
Since it seems like the quantity of training data dominates AI performance, and AI doesn't yet internalize experience with new tools, it seems like a bad idea to stray from the training set.
Obsessing over a language's syntax and semantics feels a little like debating whether you write assembly using AT&T or Intel syntax.
Some overlap here with some of my favorite essays on why SQL is lacking:
https://www.scattered-thoughts.net/writing/against-sql
That particular post ends with a wish-list of items so it's the most similar to the OP. But there are others on the site that I quite enjoy (click on the home icon and search "SQL" on the page).
My personal take is that SQL will continue to reign for a long time because of the how monumental the task of replacing it is due to the inherent complexity of databases. LLMs make this worse because they're really good at translating prose to SQL. Now that it matters less how annoying SQL is to programmers, SQL will become more like assembly over time: something mostly computers write because it's complicated for humans to deal with directly. This is deeply ironic given that SQL was ostensibly designed to read like prose, i.e. to be easy for humans.
As a meta comment, I can handle code blocks without syntax highlighting, and I can handle code blocks that wrap. But both together with long comments just turn into line noise. There's no longer any useful visual signal for how to read them. On my phone the code blocks are simply impossible to meaningfully parse.
https://www.geldata.com/blog/we-can-do-better-than-sql
(https://news.ycombinator.com/item?id=24106608, https://news.ycombinator.com/item?id=19871051)
This would have been interesting about a decade ago, but today AIs all know SQL, and I haven't written it myself in a while.
Since it seems like the quantity of training data dominates AI performance, and AI doesn't yet internalize experience with new tools, it seems like a bad idea to stray from the training set.
Obsessing over a language's syntax and semantics feels a little like debating whether you write assembly using AT&T or Intel syntax.
This is an ultra compact relational query language designed for LLMs. https://memelang.net/11/
Database engineers have to be the change they want to see and add support for newer query languages.