Engineering High-Performance Database Engines
Summary: Survey two DB engines—disk-based RDF-3X and in-memory HyPer—on architecture choices for scaling with data and hardware. Compares design decisions and optimization techniques across SPARQL and relational workloads, highlighting cross-engine trade-offs in high-performance data systems. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Thomas Neumann (Technical University of Munich)
BibTeX Citation
@article{neumann_vldb14,
title = {{Engineering High-Performance Database Engines}},
author = {Neumann, Thomas},
journal = {PVLDB},
series = {{VLDB} '14},
volume = {7},
number = {13},
pages = {1734--1745},
doi = {10.14778/2733004.2733059},
url = {https://doi.org/10.14778/2733004.2733059},
year = {2014}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,202 | Quantifying TPC-H Choke Points and Their Optimizations | 2020 | VLDB | 8.9639459e-05 |
| 2,962 | To Partition, or Not to Partition, That is the Join Question in a Real System | 2021 | SIGMOD | 7.9170451e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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