I might be off here, but this seems like the right place to ask: don't most SQL replacements focus heavily on querying while largely overlooking insertion and updating?

I get why querying gets more attention, insertions are usually straightforward and don’t need much simplification. Updates, on the other hand, can be a bit trickier since they often involve modifying data derived from complex queries. These tools seem geared toward data analysis and not data generation, which is ok: is nice focusing on a single problem and solving it "right".

But! for projects where a single person handles data creation, analysis, and management, it feels cumbersome to use one set of tools for querying ("R" in CRUD) and another for creation, updates, and deletions ("C," "U," and "D"). I think a "SQL replacement" or approach covering all of CRUD could be interesting for projects of any scale. Something that I could pick instead of shopping for ORMs and/or lightweight query generators.

More effort has definitely been focused on the 'select' aspect, since you often select more than you mutate - and even in the future state, for data warehousing cases updates can be relatively rare. I definitely don't see it targeting core OLTP CRUD work, where abstractions can sometimes cause more problems then they solve - but I hope for projects that involve bulk data creation, analysis, and management - analytics like - it can be a complete solution once the 'persist'/ 'export' queries are developed further.