You’d be trying to store a tiny bit of simple state and all the books/articles would have you standing up read only views & stored procedures for all your crud ops. The document stores came along with a fresh perspective and easy scaling.
Then their were the columnar stores and time-series stores that really did solve the newer scale problems in ways the existing sql stores didn’t.
I’m a sql guy through and through but it’s important to recognize the nosql movement was a reaction to real pain points. Also it made the sql databases better.
I have been using RDMS all along since 1996.
Nokia NetAct was scaling GB of data across multiple clusters with OLAP reporting engine in 2005 with no hiccups.
The experience I had with DynamoDB kind of proved to me I haven't lost anything by staying in the SQL path.
Most NoSQL deployments I have seen, could have been easily done in Oracle or SQL Server, provided they actually had a DBA on the team.
Mongo said “Throw data at me and I’ll scale with very little work”.
Now, I’ve always largely believed that’s penny wise and pound foolish but it’s certainly a good pitch.
One can only have bought into Mongo's story, by lacking the skills to understand how fake it was.
With those new tools you had other companies building on top of those databases for far cheaper than a license to MSSQL or any other OLAP of choice would give you.