General programming [0], static analysis [1], RDF triple stores [2], authorization systems [3], incremental computation [4] [5], graph DBs [6]. But it is kind of hard to define Datalog exactly, since it is an entire family of technologies based on logic, each extending a clean mathematical model differently.
Other than databases, program analysis. The polonius borrow checker in rustc uses datalog internally.
But you can use it for lots of things. Whenever I'm frustrated with graph based tools being slow (like build systems), I run the graph through a datalog engine for comparison. It's usually much, much faster.
Datalog is not a subset of Prolog. It looks that way because both are based on Horn clause logic, while Prolog is more expressive.
This loops Prolog, but terminates in Datalog:
p :- p.
p.
?- p.
This is because the underlying mechanism is completely different. Datalog is like SQL with recursion, you start with known facts and repeatedly applies rules to derive all consequences until nothing new appears. In Prolog, you start from the query and works backward through rules until it either finds a proof or fails.
So, Datalog treats Horn clauses as database constraints/inference rules while Prolog treats Horn clauses as a search program. They use the same mathematical substrate, but completely different computational models.
Datalog may appear to be a subset, but it is quite distinct semantically.
What is Datalog used for nowadays?
General programming [0], static analysis [1], RDF triple stores [2], authorization systems [3], incremental computation [4] [5], graph DBs [6]. But it is kind of hard to define Datalog exactly, since it is an entire family of technologies based on logic, each extending a clean mathematical model differently.
[0] https://github.com/flix/flix
[1] https://github.com/rust-lang/polonius
[2] RDFox
[3] https://github.com/eclipse-biscuit/biscuit
[4] https://github.com/vmware-archive/differential-datalog [5] https://github.com/brurucy/pydbsp
[6] https://github.com/cozodb/cozo
Other than databases, program analysis. The polonius borrow checker in rustc uses datalog internally.
But you can use it for lots of things. Whenever I'm frustrated with graph based tools being slow (like build systems), I run the graph through a datalog engine for comparison. It's usually much, much faster.
Datalog is not a subset of Prolog. It looks that way because both are based on Horn clause logic, while Prolog is more expressive.
This loops Prolog, but terminates in Datalog:
p :- p.
p.
?- p.
This is because the underlying mechanism is completely different. Datalog is like SQL with recursion, you start with known facts and repeatedly applies rules to derive all consequences until nothing new appears. In Prolog, you start from the query and works backward through rules until it either finds a proof or fails.
So, Datalog treats Horn clauses as database constraints/inference rules while Prolog treats Horn clauses as a search program. They use the same mathematical substrate, but completely different computational models.