At face value, I shudder at the syntax.
Example from their tutorial:
EmployeeName(name:) :- Employee(name:);
Engineer(name:) :- Employee(name:, role: "Engineer");
EngineersAndProductManagers(name:) :- Employee(name:, role:), role == "Engineer" || role == "Product Manager";
vs. the equivalent SQL:
SELECT Employee.name AS name
FROM t_0_Employee AS Employee
WHERE (Employee.role = "Engineer" OR Employee.role = "Product Manager");
SQL is much more concise, extremely easy to follow.
No weird OOP-style class instantiation for something as simple as just getting the name.
As already noted in the 2021 discussion, what's actually the killer though is adoption and, three years later, ecosystem.
SQL for analytics has come an extremely long way with the ecosystem that was ignited by dbt.
There is so much better tooling today when it comes to testing, modelling, running in memory with tools like DuckDB or Ibis, Apache Iceberg.
There is value to abstracting on top of SQL, but it does very much seem to me like this is not it.