There's a new Datalog [1] implementation written in the language of linear algebra (similar in nature to the ideas behind GraphBLAS [2] "graph algorithms in the language of linear algebra"). Evidently the linear-algebra approach works well for Datalog too -- the paper below shows it's the fastest Datalog implementation to date, several orders faster than the best Prolog engines.

NB: GraphBLAS runs in the recently-released RedisGraph. The Datalog linear-algebra approach is so close to simi-ring primitives in GraphBLAS. A Datalog implementation on GraphBLAS could be slick as hell. The GraphBLAS code is implemented by Tim Davis, and the code is pristine.

[1] A Linear Algebraic Approach to Datalog Evaluation (2017) [pdf] https://arxiv.org/abs/1608.00139

[2] GraphBLAS http://faculty.cse.tamu.edu/davis/GraphBLAS.html Discussion: https://hn.algolia.com/?query=GraphBLAS&sort=byPopularity&pr...