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Comment by maxdemarzi | Hacker News Reader

You can by using “narrow” tables (key value and key key). Download the slide notes from this presentation of how Relational.ai is doing it: https://www.slideshare.net/maxdemarzi/developer-intro-deckpo...

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It seems like narrow tables solve having NULLs in the tables you store, but they do nothing about NULLs in the tables you create using, say, a LEFT JOIN. Like, if you create a database with Name, Postnomials, and Prenomials, some people don't have Postnomials or Prenomials, so even if you create three narrow tables, when you JOIN them all to form the full polite addresses, you'll end up with NULLs in the result of that JOIN.

It works a little different in “Rel” (the query language Relational.ai uses). You would create multiple definitions of what a “full polite address” is for each “case” of valid arguments/empty columns and use that going forward. A bit like a UNION without the same column width requirements.

That seems clumsy.

I would think the right approach to "SQL without LEFT JOIN" would be just to focus on making pulling down multiple related tables as distinct resultsets in a single query easier and have the client code work with a graph instead of hammering everything into a single tabular layout. Or leave the concept of "connect these two tables together and make them NULL where not applicable" as an exercise for the client.

Quite the opposite. The idea is to move as much of the business logic into the database. “Rel” definitions are meant to be written once and reused everywhere. Instead of letting the client decide different business logic every time, you capture and control it in one place.

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