crepe VS datalevin

https://github.com/topics/datalog?l=rust ... Cozo, Crepe

Crepe: https://github.com/ekzhang/crepe :

> Crepe is a library that allows you to write declarative logic programs in Rust, with a Datalog-like syntax. It provides a procedural macro that generates efficient, safe code and interoperates seamlessly with Rust programs.

Looks like there's not yet a Python grammar for the treeedb tree-sitter: https://github.com/langston-barrett/treeedb :

> Generate Soufflé Datalog types, relations, and facts that represent ASTs from a variety of programming languages.

Looks like roxi supports n3, which adds `=>` "implies" to the Turtle lightweight RDF representation: https://github.com/pbonte/roxi

FWIW rdflib/owl-rl: https://owl-rl.readthedocs.io/en/latest/owlrl.html :

> simple forward chaining rules are used to extend (recursively) the incoming graph with all triples that the rule sets permit (ie, the “deductive closure” of the graph is computed).

ForwardChainingStore and BackwardChainingStore implementations w/ rdflib in Python: https://github.com/RDFLib/FuXi/issues/15

Fast CUDA hashmaps

Gdlog is built on CuCollections.

GPU HashMap libs to benchmark: Warpcore, CuCollections,

https://github.com/NVIDIA/cuCollections

https://github.com/NVIDIA/cccl

https://github.com/sleeepyjack/warpcore

/? Rocm HashMap

DeMoriarty/DOKsparse:

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

You can also consider other durable Datalog options like datahike or datalevin which can work either as lib (SQLite style) or in a client-server setup; if you want to play with bi-temporality XTDB is a rock solid option with very good support and documentation.

There are some Clojure-ecosystems things that are pretty cool, too, that you'd probably miss going into Haskell. lacinia is an extremely cool GraphQL library, and there are a variety of interesting datalog-based datastores which are spiritual descendents of Datomic, notably xtdb (formerly crux) and datalevin. Also as noted, you can write the front-end in ClojureScript if you want to, and there are a lot of cool libraries for that as well.

There are plenty of open source Datomic Inspired databases. Check out https://github.com/juji-io/datalevin and scroll down all the way down to “Alternatives”. There was even the beginning of a rust one by Mozilla: https://github.com/mozilla/mentat

The benchmarks in question have several implementation issues, I reported them on GitHub.

https://github.com/juji-io/datalevin/issues/created_by/caval...

Highly recommend you give https://github.com/juji-io/datalevin a chance. You can use it both as a key-value and/or relational datalog store (like datomic) but it’s very simple to set up and blazing fast!

Unlike some other commenters, I agree that graph models are usually a better fit for most data than relational models. There's been some interesting work in recent years developing this idea: in the Clojure world there's Datomic, XTDB, and a host of competitors, all of which build on work from Semantic Web/SPARQL/triplestores and logic programming. Some are even intended to be used as primary datastores: they support some amount of schema and constraints, have well-defined consistency and ACID guarantees, etc. This makes them unlike graph databases like Neo4J and others, which fill an architectural role more like Elasticsearch as a read-optimization tool. Here's an interesting talk making a case for triple-based databases.