AvantGraph is a research-oriented graph analytics engine designed for processing navigational graph queries and subgraph matching on property graphs. It targets analytical workloads and focuses on advanced query planning techniques, including worst-case optimal joins and regular queries with memory.
Key research milestones include work on hybrid worst-case optimal query planning, fully compiled execution of conjunctive graph queries, and structural in-memory graph factorization.
AvantGraph is a research-oriented graph analytics engine designed for processing navigational graph queries and subgraph matching on property graphs. It targets analytical workloads and focuses on advanced query planning techniques, including worst-case optimal joins and regular queries with memory.
Key research milestones include work on hybrid worst-case optimal query planning, fully compiled execution of conjunctive graph queries, and structural in-memory graph factorization.
History[02]
AvantGraph originated from a series of master's theses and academic publications from Eindhoven starting around 2019. The system was formally introduced with a PVLDB publication in 2022. Subsequent research has expanded its capabilities to include cardinality estimation advisors, temporal network modeling, and property graph data management optimizations.