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RDFox uses datalog to apply inference rules to graph data, it has some state of the art algorithms for making datalog multi-core. It still uses SparQL, which is

RDFox uses datalog to apply inference rules to graph data, it has some state of the art algorithms for making datalog multi-core. It still uses SparQL, which is really similar to datalog for querying. There's some recent work on horizontally scaling datalog queries, but I hadn't seen anything in production. Probably the most popular implementation is datomic and its free variants. Which has a lot of convenience to it as you can embed custom java functions. It's not datalog but cypher has a lot of amazing ideas like easily combining algorithms to potentially recursive relationship queries, eg, "Give me the all shortest paths between these two peoples where there's at most 6 hops" -> allShortestPaths((n1:Person)-[*..6]->(n2:Person)) .

refset 7y ago
I work on Crux [0], which is also a Java-friendly Datalog database. It sits on top of lazy EAV indexes in RocksDB/LMDB so it's pretty fast and scales well (though technologies like Neo4j/GraphBLAS will be faster!). We don't have online REPL just yet but Nextjournal is pretty great if you want to play through the tutorials interactively [1]. The other unique angle is that Crux gives you "bitemporal" Datalog queries. Oh and the MIT license :) [0] https://opencrux.com https://opencrux.com [1] https://nextjournal.com/crux-tutorial/ https://nextjournal.com/crux-tutorial/