Incroxigraph
Extend Oxigraph with continuous live evaluation of SPARQL queries
Dynamic applications, such as real‑time dashboards, local‑first clients, IoT analytics, and collaborative data platforms, increasingly require SPARQL queries that react instantly to changing RDF data. Today, most engines fully recompute query results, causing unnecessary delays. This project introduces Incroxygraph, which extends Oxigraph (a fast, Rust‑based graph database implementing the SPARQL standard) to support Incremental View Maintenance (IVM) for SPARQL queries. By updating query results incrementally as data changes, Incroxigraph will enable highly responsive SPARQL applications with significantly lower latency and computation overhead. The work re‑implements proven incremental techniques in Rust and delivers them as an open‑source, production‑grade engine with bindings for Python and potentially WebAssembly/JavaScript. A key integration target is NextGraph, a decentralized CRDT‑driven platform where Incroxigraph will allow efficient querying over continuously evolving, collaborative data. The resulting technology will strengthen the open Linked Data ecosystem by making responsive SPARQL evaluation broadly accessible for modern, data‑intensive, and decentralized applications.
- The project's own website: https://github.com/comunica/incremunica
Run by imec
This project was funded through the NGI0 Commons Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 101135429. Additional funding is made available by the Swiss State Secretariat for Education, Research and Innovation (SERI).
