TL;DR
Nemo is a new logic programming engine designed for reliable, high-performance data-centric analytic computations using a declarative Datalog dialect, capable of handling large knowledge graphs efficiently.
Contribution
It introduces Nemo, a scalable, Rust-based Datalog engine optimized for reasoning over large knowledge graphs on standard hardware.
Findings
Nemo matches or exceeds the scalability of leading Datalog systems.
It efficiently handles 10^5 to 10^8 facts on a laptop.
Nemo is open source and suitable for knowledge graph reasoning.
Abstract
This system demonstration presents Nemo, a new logic programming engine with a focus on reliability and performance. Nemo is built for data-centric analytic computations, modelled in a fully declarative Datalog dialect. Its scalability for these tasks matches or exceeds that of leading Datalog systems. We demonstrate uses in reasoning with knowledge graphs and ontologies with 10^5 to 10^8 input facts, all on a laptop. Nemo is written in Rust and available as a free and open source tool.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsFocus
