snakelog VS datascript

You can without too much work transpile datalog to SQL. SQL does have such strong support that it is useful https://github.com/philzook58/snakelog or perhaps just do it manually https://www.philipzucker.com/tiny-sqlite-datalog/

Very cool! I love the sqlite install everywhere model.

Could you compare use case with Souffle? https://souffle-lang.github.io/

I'd suggest putting the link to the docs more prominently on the github page

Is the "traditional" datalog `path(x,z) :- edge(x,y), path(y,z).` syntax not pleasant to the modern eye? I've grown to rather like it. Or is there something that syntax can't do?

I've been building a Datalog shim layer in python to bridge across a couple different datalog systems https://github.com/philzook58/snakelog (including a datalog built on top of the python sqlite bindings), so I should look into including yours

Hi pests, I don't think the criticism in the comments gives a full picture.

I wrote about a particular flavor of datalog, in common use today. [1] [2]. The earliest representation I know, which matches the syntax of my essay, was in SICP [3]

There's another, more academic form of datalog, which looks a lot more like prolog. Both have lots of similarities: both systems have a set of facts and rules. Both systems have can take a partially filled fact or rule, and find all matching facts. The more academic flavors of Datalog are useful for general logic, and particularly powerful for recursive questions. The variant I showed is more tailed for database queries.

[1] https://github.com/tonsky/datascript

There is also datascript as a similar option.

What's the use case for relic? Sounds similar to https://github.com/tonsky/datascript ?

This look nice !

Datascript seems to be another Datalog engine (in memory only)

https://github.com/tonsky/datascript

Inspired by past work: LINQ, inline-python, crepe, DataScript, Riffle.

An in-memory database like Datascript may be worth looking into. Otherwise you could take an indexing approach: put all the data into one big map indexed by some unique key, and have a bunch of supplementary indexes that are updated on insertion.