The databases we use today in production have severe limitations and are not even close to what is theoretically possible. Many traditional parts of a database (indexing, caching, scheduling, et al) are AI-complete algorithm problems. Entire sub-classes of database (e.g. graph or spatial) famously have persistently poor scalability and performance because of open questions in the foundational computer science.

Just the fact that increasing the generality, scalability, and performance of databases asymptotically converges on designing AGI suggests that it is, in fact, "deep tech". And this property has to mesh with other practical constraints on database behavior. Many problems in databases are hard with little forward progress in decades.

It is true that most database research is not deep tech but there is ample room for it to be if one is sufficiently ambitious.

Maybe only an OS can be close to how MUCH deep you can go with a DB engine.

And I bet DB engines can go far than normal OS.

You don't know how much is still waiting for somebody to try, and how much is not applied. And how many of that DBs are not even doing, because all are constrained be being "apps" with so poor interface (sql).

Fun fact: Not exist a viable true relational DBs implemented, neither exist one with a viable programming language AND apis that is for developers.

ZERO.

I'd ascribe "deep tech" to anything that you can reasonably get a PhD in and have it not be unusual. There are dozens of academic conferences on DBs pushing the frontier forward.