#GQL

The open-source Rust library #gql-rs turns Graph Query Language queries into a typed syntax tree and checks them for logical correctness. It follows the ISO/IEC 39075:2024 standard and was released by NTUR LAB as part of its AUREA suite, which aims at a sovereign, vendor-neutral data ecosystem

https://ntur-lab.com/gql-parser/

Virtuoso DB now support built-in Graph Algorithm as part of #GQL. Here is you can execute the Pagerank algorithm on Social Network

#GQL
USE GRAPH <urn:social>
MATCH (a)-[:foaf:knows]-(b)
RETURN DISTINCT a,
  bif:pagerank(
    a
) AS score

Try it out here:
https://vec.demo.openlinksw.com/...eout=0&signal_void=on

AgensGraph 2.18, built on #PostgreSQL 18.6, introduces expanded support for the ISO #GQL standard alongside openCypher to enable more robust graph database operations. This release enhances performance by optimizing variable-length traversals to utilize edge label indexes, and it adds typed-column property promotion to improve indexability of JSONB properties.

https://tech.skaiworldwide.com/downloads/?lang=en

The Virtuoso #GQL + RDF Extension implements the ISO/IEC 39075:2024 Graph Query Language as a translation layer atop Virtuoso’s SPARQL engine, allowing property-graph queries over RDF data held in its quad store and thereby connecting the ISO #GQL standard with the W3C RDF/SPARQL ecosystem.#GQL queries are converted to SPARQL for execution by Virtuoso’s optimized engine (including its cost-based optimizer, transitive paths and geospatial indexing), while INSERT, DELETE, SET, REMOVE and MODIFY operations map to SPARQL Update for atomic changes; Virtuoso-specific features such as inference, owl:sameAs, geospatial functions and RDF 1.2 triple terms remain accessible through VERSION, DEFINE and OPTION clauses.

https://www.openlinksw.com/virtuoso/docs/gql/#gql-overview

froGQL is an open-source graph database that integrates property graphs, schemas, and indexes into a single file to operate within host applications, similar to SQLite, while implementing the ISO #GQL standard. Its engine leverages the Leapfrog Triejoin algorithm for worst-case optimal query evaluation, significantly improving performance by avoiding the construction of intermediate results. Additionally, the system features a gradual type system designed to detect and prune queries with type mismatches before execution.

https://sferrada.com/pdf/froGQL-ISWC2026.pdf