Personally I think that's worse. SQL - which is almost ubiqutous - already suffers from a fragmentation problem because of the complex and dated standardization setup. When I learn a new DBMS the two questions I ask at the very start are: 1. what common but non-standard features are supported? 2. what new anchor-features (often cool but also often intended to lock me to the vendor) am I going to pick up?

First I need to learn a new (even easy & familiar) language, second I need to be aware of what's proprietary & locks me to the vendor platform. I'd suspect they see the second as a benefit they get IF they can convince people to accept the first.

I actually 100% agree with your for a new DBMS and share your frustration with vendor-specific features and lock-in. At that level, it's often actively counterproductive for insurgent DBs - ecosystem tooling needs more work to interface with your shiny new DB, etc - and that's why we always see anyone who starts with a non-standard SQL converge on offering ANSI SQL eventually.

I think an application that exposes a curated dataset through a SQL-like interface - so the dashboard/analytic query case described here - is where I think this approach has value. You actually don't want to expose raw tables, INFORMATION_SCHEMA, etc - you're offering a dedicated query language on top of a higher level data product offering, and you might as well take the best of SQL and leave the bits you don't need. (You're not offering a database as a service; you're offering data as a service).