Hacker News Reader

Comment by burakemir | Hacker News Reader

Here is a proof that you can translate non-recursive datalog into relational algebra and vice versa: https://github.com/google/mangle/blob/main/docs/spec_explain...

Since Logica is translated to SQL it should benefit from all the query optimistic goodness that went into the SQL engine that runs the resulting queries.

I personally see the disadvantages of SQL in that it is not really modular, you cannot have libraries, tests and such.

Disclosure: I wrote Mangle (the link goes to the Mangle repo), another datalog, different way of extending, no SQL translation but an engine library.

View on HN

Mangle looks very interesting, thanks for the share. In particular I love your GRPC demo, because it shows a prototype of something I've been thinking about for a long time: what if we did GraphQL, but with Datalog! Maybe we could call it LogiQL :)

In particular many people talk a lot about concerns like optimizations across GraphQL plans and how they are expected to behave on underlying tables, but this is something that I think has seen a lot of research in the Datalog realm. And to top it off, even ignoring that, Datalog just feels much more natural to write and read after a bit of practice, I think. (Obviously you need to be in the pure fragment of datalog without recursion, but even then it might be feasible to add those features with termination criteria even if it's just "decrement an internal counter and if it hits zero throw a big error")

What do you think the plans for the Rust implementation will be? That's probably the most likely place I'd use it, as I don't really use Go that much.

The Mangle repo has the beginnings of a Rust implementation but it will take some time before it is usable. The go implementation is also still being improved, but I think real DB work with persistent data will happen only in Rust. Bindings to other host languages would also use the Rust implementation. There are no big challenges here it is just work and takes time.

The combination of top-down and bottom up logic programming is interesting, especially when one can move work between pre computation and query time.

I like that optimizing queries in datalog can be discussed like optimization of programming language but of course the biggest gains in DB come from join order and making use of indices. There is a tension here between declarative and having some control or hints for execution. I haven't yet figured out how one should go about it, and also how to help programmers combine top-down and bottom-up computation. Work in progress! :-)

Reply on news.ycombinator.com