AvantGraph Query Processing Engine
Summary: AvantGraph is a graph-query engine targeting both subgraph matching and navigational queries. Its distinctive design jointly advances planning, cardinality estimation, and execution, with demonstrations exposing optimizations across diverse workloads. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wilco v. Leeuwen (Eindhoven University of Technology)
- 2. Thomas Mulder (Eindhoven University of Technology)
- 3. Bram van de Wall (Eindhoven University of Technology)
- 4. George Fletcher (Eindhoven University of Technology)
- 5. Nikolay Yakovets (Eindhoven University of Technology)
BibTeX Citation
@article{leeuwen_vldb22,
title = {{AvantGraph Query Processing Engine}},
author = {Leeuwen, Wilco v. and Mulder, Thomas and van de Wall, Bram and Fletcher, George and Yakovets, Nikolay},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {12},
pages = {3698--3701},
doi = {10.14778/3554821.3554878},
url = {https://doi.org/10.14778/3554821.3554878},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,797 | NeuSO: Neural Optimizer for Subgraph Queries | 2026 | SIGMOD | 5.1257999e-05 |
| 9,980 | Schema-Based Query Optimisation for Graph Databases | 2025 | SIGMOD | 5.1013913e-05 |
| 10,962 | GraphAlg Playground: An Online Platform for Learning and Experimenting with the GraphAlg Language | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 373 | Umbra: A Disk-Based System with In-Memory Performance | 2020 | CIDR | 0.00019711632 |
| 540 | An Analytical Study of Large SPARQL Query Logs | 2018 | VLDB | 0.00016726545 |
| 860 | G-CORE: A Core for Future Graph Query Languages | 2018 | SIGMOD | 0.00013406849 |
| 1,596 | Adopting Worst-Case Optimal Joins in Relational Database Systems | 2020 | VLDB | 0.00010127607 |
| 2,137 | Quickstep: A Data Platform Based on the Scaling-Up Approach | 2018 | VLDB | 8.9777553e-05 |
| 3,420 | Query Planning for Evaluating SPARQL Property Paths | 2016 | SIGMOD | 7.3147525e-05 |
| 4,605 | Worst-Case Optimal Graph Joins in Almost No Space | 2021 | SIGMOD | 6.5047683e-05 |
| 5,050 | On the Optimization of Recursive Relational Queries: Application to Graph Queries | 2020 | SIGMOD | 6.2976106e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 719 | Querying Graph Databases | 2013 | PODS |
| 2 | 12,165 | NAVIGATE: Explainable Visual Graph Exploration by Examples | 2019 | SIGMOD |
| 3 | 3,798 | All-in-One: Graph Processing in RDBMSs Revisited | 2017 | SIGMOD |
| 4 | 6,485 | Modern Techniques for Querying Graph-Structured Relations: Foundations, System Implementations, and Open Challenges | 2022 | VLDB |
| 5 | 6,713 | G-SQL: Fast Query Processing via Graph Exploration | 2016 | VLDB |
| 6 | 10,270 | GraphMatch: Subgraph Query Processing on Steroids | 2026 | SIGMOD |
| 7 | 8,330 | Computing How-Provenance for SPARQL Queries via Query Rewriting | 2021 | VLDB |
| 8 | 9,027 | Generating Flexible Workloads for Graph Databases | 2016 | VLDB |
| 9 | 288 | Graphs-at-a-time: Query Language and Access Methods for Graph Databases | 2008 | SIGMOD |
| 10 | 2,014 | RapidMatch: A Holistic Approach to Subgraph Query Processing | 2021 | VLDB |