G-SQL: Fast Query Processing via Graph Exploration
Summary: G-SQL fuses an in-memory graph engine with an RDBMS to accelerate graph exploration and multi-way joins. A SQL dialect augmented with graph exploration dispatches tasks to both runtimes under a unified cost model; experiments show expanded capabilities and strong SQL-graph performance. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hongbin Ma
- 2. Bin Shao
- 3. Yanghua Xiao
- 4. Liang Jeff Chen
- 5. Haixun Wang
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,143 | Extracting and Analyzing Hidden Graphs from Relational Databases | 2017 | SIGMOD | 7.4804326e-05 |
| 5,338 | Fast In-Memory SQL Analytics on Typed Graphs | 2017 | VLDB | 5.5629772e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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