[tibiapejagala]

The problem with sql is what happens when you fall off the SELECT FROM JOIN WHERE GROUP BY HAVING ORDER BY LIMIT cliff. The simple stuff in sql reads like English, but for that case ORM would generate a pretty efficient query anyway. The complex stuff in sql looks terrible in my experience and ORM bail out quickly. Once you can’t get the result with a simple SELECT then sql stops being declarative. Instead of writing what you want to get, you write something like a postmodern poem while having a stroke, just to convince postgres benevolent spirits to give you something almost right. Complex UPDATEs and DELETEs with joins are even worse.

Also lack of syntax sugar doesn’t help. SELECT list could support something like “t1.* EXCEPT col1, col2”. Maybe JOIN ON foreign key would be nice. IS DISTINCT FROM for sane null comparisons looks terrible. Aliases for reusing complicated statements are really limited. Upsert syntax is painful. Window functions are so powerful that I can’t really complain about them though.

We use a lot of sql for business logic, but some code I have to reread from zero every time I need it. Maybe we modeled our data wrong or there is some inherent complexity you can’t avoid, but I mostly blame sql the language. Unfortunately I have no idea how it could be improved.

Anyway I think the sql cliff is real. Once you take a step outside the happy path prepare for a headache. For me sql definitely is in some local maxima, after all I use it every day at work.

[oblio]

The biggest thing is... SQL is not reusable, period.

Why don't we have SQL libraries?

I know that data models are kind of special snowflakes, but some models pop up over and over and over again and code reuse is always 0 with SQL.

To give you an example of a common problem, SLAs or the like for teams with regular business hours.

A team has to respond to a request within N hours. To calculate that I need to take into account 8 business hours per day, excluding weekends, excluding holidays (ideally localized holidays), etc.

It's a nightmare with SQL. It's precisely the kind of thing you want in a library.

Plus, obviously, standard SQL doesn't have a way to share and distribute any libraries, even if they were made. It's pre-C in terms of stuff like that.

[BatteryMountain]

And the core issue is, sql is just strings. It only fails at runtime and not a compile time. There is no compile-time strong/static typing, you only find out its broken when you run it. So it makes it really difficult to re-use. The other problem is, you have to specify table and column names in queries (duh, how else), but that means the entire persistence model is hard coded and need manual tweaking and so on. In an ideal universe, each field would be generic, each object generic and each collection of objects generic and all functions being generic. You'd end up with one huge flat structure of fields that are linked to each other to form more complex objects. But that not efficient in current computers nor do we have enough memory to store all information like that. And you might end up back at square one where everything is just strings.

[mulmen]

The data model is the code reuse.

You can model business hours and SLAs with relationships. Join on time and team.

  SELECT support_request.request_time + team.response_sla AS respond_by_time
  FROM support_request 
  JOIN team_sla 
    ON support_request.assigned_team = team_sla.team_id
   AND DATE_PART('day', support_request.request_time) = team_sla.day_of_week
   AND DATE_PART('hour', support_request.request_time) BETWEEN team_sla.start_hour AND team_sla.end_hour;

[uvdn7]

SQL is not modular (the root cause of why it’s hard to reuse) because it’s declarative. If the underlying data models stay relatively stable, you can reuse code with certain assumptions. There’s a trade off here for sure.

[wppick]

SQL can be somewhat reusable through views. Also in your code you can make reusable functions that contain SQL queries. You won't get the best performance reusing the queries this way, but you can put them into a transaction and build up more complex flows from reusable pieces that way

[jbverschoor]

Postgis and many other libraries exist. They are widely used.

[BatteryMountain]

No man you are right. There is nothing arcane here: sql is just an ugly and unintuitive language. I think sql works the opposite ways normal brains work so unless you are doing a simple query, you have to be able to parse and simulate what sql will do in your head. After doing functions/MV's with CTE's that are 100+ lines per query daily, you kinda get used to but also not. I've concluded that although sql is awesome, it is also full of warts.

What helps me is to code all of it in lower case and use something like that Datagrip with a good theme. That way you get something that is readible, colour coded and has autocomplete (very good with joins). It's the only way I've managed to keep my sanity as my experience with it grew. Bad data models doesn't reallllly impact it that much, sql is still sql even with a clean model.

I've built mini database engines in the past because of my frustrations with sql but I still use and prefer an actual rdms as opposed to trying to reinvent the wheel. There are so many features we take for granted it's not even funny. Try building your own production-ready storage system and you would quickly appreciate how deep the rabbit hole really goes.

[hiptobecubic]

I have used those features that you say "Would be nice to have." I didn't realize they weren't ubiquitous. I agree they are excellent.