I think people need to realize that HTAP it's not a technology but database features while relational is the real database technology.
It seems that now people is converging to this pseudo-math database solution namely Postgresql with its battle-hardened object-relational technology that's IMHO a local minima [1].
The world need a proper math based universal solution for the database technology similar to relational. But this time around we need much more features, we want it all including analytical, transaction, spreadsheet, graph, vector, signal, etc. On top of that we want reliable distributed architecture. We simply cannot add on indefinitely upon Postgresql because the complexity will be humongous and the solutions become sub-optimal [2].
We need strong database foundation with solid mathematical basis not unlike the original relational database technology.
The best candidate that's available now is D4M by the fine folks at MIT that has been implemented in Matlab, Python and Julia [3]. Perhaps someone need to write C++, Dlang or Rust version of it to be widely acceptable.
It's funny that the article started by mentioning the article inspiration was from the popular article on big data is dead and by doing so is prematurely dismissing the problem. The book on D4M, however embrace the big data problem by its head by putting the exact terminology it the title [4].
[1] What’s the Difference Between MySQL and PostgreSQL?
https://aws.amazon.com/compare/the-difference-between-mysql-...
[2] Just Use Postgres!
https://www.manning.com/books/just-use-postgres
[3] D4M: Dynamic Distributed Dimensional Data Model:
[4] Mathematics of Big Data: Spreadsheets, Databases, Matrices, and Graphs (MIT Lincoln Laboratory Series):
https://mitpress.mit.edu/9780262038393/mathematics-of-big-da...