That's my hunch too. Prolog is a different world and you still want to keep one foot in more mainstream languages. The idea should be use Prolog where it gives real advantages and use mainstream languages where it doesn't. So how do you divide your application into those two "islands"? Answer: Use persistent Datalog for database/persistence but do the rest in you bread-and-butter language.
Basically saying replace SQL with Datalog.
That is just what I think I'd like to do. I don't know what would be the most practical platforms to do that, which mainstream language + which Datalog database. Any recommendations?
No recommendations, sorry, merely a couple of thoughts.
Prolog and datalog start out as rather different beasts, though prolog tabling gets them closer. It's an area of current research[1].
A datalog implementation can serve as DSL, learning tool, and/or efficient solver of large problems. For the first two, most languages have a little datalog implementation or three.
For datalog engines, perhaps Z3 and its fixpoint engine from python?? Or maybe Soufflé from python?? But I really have no idea what's plausible. I too would be interested.
> database/persistence
That's something with a big diverse active market. Datalog engines, not so much. So I'm unclear that datalog is a place to go for that? But I also pay no attention to non-open-source offerings.
Basically saying replace SQL with Datalog.
That is just what I think I'd like to do. I don't know what would be the most practical platforms to do that, which mainstream language + which Datalog database. Any recommendations?