SQLDelight VS jOOQ

This seems to be similar to https://github.com/cashapp/sqldelight, and I've always wanted a python equivalent!

In typescript, there are query builders (not talking about ORMs) that can basically do this within the type system, but that would be infeasible in python's type system. This approach (type/code generation is a good alternative, though I like using sqlalchemy / alembic to manage schemas/migrations.

One thing I'm curious about is how it knows the types of columns? I looked quickly at the Readme but didn't see it (probably a parameter somewhere I missed).

That functionality has existed for almost exactly a year

- SQLDelight - great experience overall, the only issue that I found, was when that I made a database migration that worked on Android, but not on iOS (https://github.com/cashapp/sqldelight/issues/3812)

Database - SQLDelight

room is a great example but like I said our data is kotlin-only so we tend to use libraries like sqlDelight.

This seems similar to https://cashapp.github.io/sqldelight/ for kotlin, I think this approach is pretty neat, good luck with it!

Sounds like you want what SQLDelite offers, but for TypeScript. SQLDelite is only for Kotlin and SQLite though.

SQLDelight had neat built in support for this

https://cashapp.github.io/sqldelight/

Relational databases provide components such as cursors, which can be used to process large datasets while fetching only a limited number of rows at a time. With the help of jooq framework,we can take it a step further—leveraging cursors under the hood while seamlessly integrating with Java's Stream API. Let’s see it in action!

(1) DSLs work great sometimes. See https://www.jooq.org/

(2) Elastic Load Balancer is a control loop responsive to workloads, that kind of thing is a commodity

(3) Under-provisioning is rampant in most industries; see https://erikbern.com/2018/03/27/waiting-time-load-factor-and... and https://www.amazon.com/Goal-Process-Ongoing-Improvement/dp/0...

(4) Anomaly detection is not inherently a problem of distributed systems like the others, but someone facing the problems they've been burned with might think they need it. Intellectually it's tough. The first algorithm I saw that felt halfway smart was https://scikit-learn.org/1.5/modules/outlier_detection.html#... which is sometimes a miracle and I had good luck using it on text with the CNN-based embeddings we had in 2018 but none at all w/ SBERT.

jOOQ would be one such example, https://www.jooq.org/

Not that I use this, I am a myBatis person in what concerns database access in Java, and Dapper in .NET for that matter, not a big ORM fan.

> 2. ORMs do not hide SQL nastiness.

This is certainly true!

I mean: ORMs are now well known to "make the easy queries slightly more easy, while making intermediate queries really hard and complex queries impossible".

I think the are of ORMs is over. It simply did not deliver.

If a book on SQL is --say-- 100 pages, a book on Hibernate is 400 pages. So much to learn just to make the easy queries slightly easier to type? Just not worth it.

I prefer jooq any day over ORMs. And dont get me started over what tools like Hasuna have to offer.

There are also some languages (forgot the names) that are SQL-done-right. Select in the back, more type safe, more logic, more in the same steps as the query gets executed. These need to be adopted by PG and MySQL and we're good to go. (IMHO)

https://www.jooq.org/

https://hasura.io/

See: https://github.com/jOOQ/jOOQ/issues/5916

Spring Boot, ili ako bi nesto vise lightweight u Javi Spark + jOOQ