rust-datalog

What problem does it solve?

Datalog reasoning in Rust can be complex, expensive, and error-prone when built from scratch. This Skill documents in-memory implementations and patterns using the datafrog, crepe, and ascent ecosystems to enable fast, correct fixed-point computations within Rust programs.

Core Features & Use Cases

• In-memory, bottom-up evaluation for Datalog queries leveraging datafrog (Polonius), crepe (proc-macro), and ascent (lattices).
• Demonstrates common operations: fixpoint iteration, joins (including anti-join), stratification, and lattice-based reasoning for advanced analyses.
• Use Case: build high-performance static analyses or dataflow engines inside Rust projects without external databases.

Quick Start

Load a small edge dataset and run the transitive-closure example to observe the fixpoint convergence.