21–30 of 44 posts
> CQL is not a database management system: it neither stores nor updates data. The same could be said for SQL. How does CQL differ from SQL? If I squint my eyes just a tiny amount, these ideas become really difficult to separate. I was always under the impression that the relational model is based upon many concepts studied in category theory. To my mind, all of the following things are overlapping parts of the exact…
As best as I can tell (but i really dont know much about databases) it's probably a narrow advantage - storage and everyday queries still go to Codd's model - but for stitching schemas together it seems like it could work.
I'm using similar math for automated formal verification, where this approach is what makes it tractable.
Earlier quoted context omitted.
"how to accomplish the thing." I always thought this was splitting hairs. C#,C++, Java seems imperative. You are in control? But you aren't really telling it how to move values between registers, the compiler is making a million decisions for you on how the computer will execute that 'imperative' code. Just like SQL isn't really telling the DB how to do it either..
It's really a matter of degrees though. You're waving away a big part of the big sell of a relational database as proposed by Codd, which is that the user need not "know" the structure of the data in order to formulate operations on it because there's a consistent set-oriented model that can be used with a bunch of different physical storage forms but also the very sequence of relational operations against it can be…
> CQL is not a database management system: it neither stores nor updates data. The same could be said for SQL. How does CQL differ from SQL? If I squint my eyes just a tiny amount, these ideas become really difficult to separate. I was always under the impression that the relational model is based upon many concepts studied in category theory. To my mind, all of the following things are overlapping parts of the exact…
Most attempts to replace/improve SQL derive from the fact SQL was a poorly conceived and designed interface, that originally was meant to be a very small DSL for end users, but unfortunately, was allowed to become a poor, complicated, confusing mess for app developers:
https://cacm.acm.org/research/50-years-of-queries/
SQL is not an orthogonal language... This is because, in the early days, Ray Boyce and I did not think we were designing a language for programmers. ..
As it turned out, Ray and I were wrong about the predominant usage of SQL...
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So the #1 thing any actual replacement or alternative to SQL is how actually become a good language for development, so it is actually composable, can be actually be used to reason about it, has minimal foot guns, etc.
There is a lot of misunderstanding and pushback, similar to how people in the past fight improvements over JS/C/C++ until typescript, rust comes.
But, oh boy, SQL need their typescript!
> Reduce risk of failure through artificial intelligence. CQL contains an embedded automated theorem prover that guarantees the correctness of CQL programs. Man, it's a rough environment right now marketing-wise. I don't know if they're contractually obligated to say the funny magic words, but the term AI is nearly entirely meaningless at this point. Akin to saying "behold my mighty calculator app: it prevents divisi…
AI agents fielded by major AI players still fail at the basic task of providing immediate and correct support for use of the current versions of their products. If a programming language is too new to have adequate representation in the training corpus, there isn't an accepted standard way to provide a reference manual targeting AI agents. Even the best way to include documentation in a large project so new AI agents can take over is controversial. A pile of linked markdown files really isn't an answer, less structured than a codebase itself, that AI is good at navigating.
Other HN posts have discussed using SQL as a backbone for the AI "mind mapping" support we need for AI more critically than for ourselves.
I was hoping that CQL could be an answer to this. Perhaps, but not its current primary goal.
> CQL is not a database management system: it neither stores nor updates data. The same could be said for SQL. How does CQL differ from SQL? If I squint my eyes just a tiny amount, these ideas become really difficult to separate. I was always under the impression that the relational model is based upon many concepts studied in category theory. To my mind, all of the following things are overlapping parts of the exact…
The main innovation here seems to be compile time checking of that foreign keys are respected but that is a thing that can be added to SQL and there is at least one proposal for doing so. So I do not really see anything fundamentally different from SQL. https://keyjoin.org/ Full disclosure: I am one of the co-authors of this paper and an associated patch implenting it in PostgreSQL that we have proposed. I am happy t…
> Reduce risk of failure through artificial intelligence. CQL contains an embedded automated theorem prover that guarantees the correctness of CQL programs. Man, it's a rough environment right now marketing-wise. I don't know if they're contractually obligated to say the funny magic words, but the term AI is nearly entirely meaningless at this point. Akin to saying "behold my mighty calculator app: it prevents divisi…
Maybe that's my bias since that's what I'm working on, but it's a big benefit to have stronger compiler guarantees of correctness so that an LLM can't screw things up as much. No BSing that it works when the compiler requires proof.
> CQL is not a database management system: it neither stores nor updates data. The same could be said for SQL. How does CQL differ from SQL? If I squint my eyes just a tiny amount, these ideas become really difficult to separate. I was always under the impression that the relational model is based upon many concepts studied in category theory. To my mind, all of the following things are overlapping parts of the exact…
(edit: in retrospect, this is just the "getting started" header link, despite the URL)
Unfortunately none that I've followed seems to do much to describe much of anything except the math foundations. They might cover pieces of syntax, but not how to use or think about them, and they seem to be rather excited about the data-generating features that I can't imagine anyone using outside tech demos (unless that's the only insert method? what about update?) :/
(edit 2: you can't even rely on the manual apparently, I'm fairly confident https://categoricaldata.net/help/Demo.html (manual -> examples -> demo) won't work because it has no schema definition for `Animal`. and it like all the others I've checked are little more than syntax and output, no real explanation)
Earlier quoted context omitted.
> How does CQL differ from SQL? SQL is like Java, CQL is like Haskell. SQL has been around and used in production. CQL is a research language, possibly cleaner foundation but YMMV. The math fields you list are connected, but whether they are the same monster - again it's kinda like claiming all programming languages and implementations are the same (Turing-complete?) monster.
SQL is not an imperative programming language.