BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers
Summary: Introduces BYO, the first unified framework to benchmark graph containers (not whole systems) by running 10 optimized algorithms across 20+ containers and 10 graphs, supporting dynamic updates and batch-insert measurements for apples-to-apples comparison. Finds container design impacts performance far less than expected—an off-the-shelf B-tree is only ~1.22x slower than a tuned static container and a minimal API costs ~1.16x—suggesting simpler, general-purpose containers are viable for large-scale graph analytics. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Brian Wheatman
- 2. Laxman Dhulipala
- 3. Xiaojun Dong
- 4. Jakub Łącki
- 5. Zheqi Shen
- 6. Prashant Pandey
- 7. Helen Xu
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,161 | Enabling Efficient Direct Update on Rule-Based Compressed Graph | 2026 | SIGMOD | 4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.