ego VS asami

Shameless plug, I also maintain an OCaml implementation of egraphs (named ego) at https://github.com/verse-lab/ego

While the most popular implementation at the moment seems to be egg in Rust, I find that OCaml serves as a much more ergonomic environment for quickly prototyping out uses of egraphs in practice. As a bonus, ego also shares the same logical interface as egg itself, so once you've finalised your designs, you shouldn't have much trouble porting them to egg if you need the performance gains.

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.

Despite the documentation that exists, I've heard many people who have been confused about how to query Datomic, Datascript, Asami, or other graph databases. So I've made an attempt at explaining it https://github.com/threatgrid/asami/wiki/Introduction

The first Graph implementation for Asami was a simple in-memory data structure, described in my ClojureD talk. The code for this appears in asami.index. This file started much smaller (as referenced above), but has since expanded with the needs extended functionality, such as transactions, and transitive closure operations.