VectorH: Taking SQL-on-Hadoop to the Next Level
Summary: VectorH extends SQL-on-Hadoop by layering Vectorwise on HDFS for fault-tolerant storage with read-locality via replication policy. PDT-based trickle updates enable update-averse tables; YARN-enabled MPP with Spark yields substantial gains over Hive/Impala. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Andrei Costea (Actian)
- 2. Adrian Ionescu (Actian)
- 3. Bogdan Rǎducanu (Actian)
- 4. Michał Świtakowski (Actian)
- 5. Cristian Bârcă (Actian)
- 6. Juliusz Sompolski (Actian)
- 7. Alicja Łuszczak (Actian)
- 8. Michał Szafrański (Actian)
- 9. Giel de Nijs (Actian)
- 10. Peter Boncz (Centrum Wiskunde & Informatica)
BibTeX Citation
@inproceedings{costea_sigmod16,
title = {{VectorH: Taking SQL-on-Hadoop to the Next Level}},
author = {Costea, Andrei and Ionescu, Adrian and Rǎducanu, Bogdan and Świtakowski, Michał and Bârcă, Cristian and Sompolski, Juliusz and Łuszczak, Alicja and Szafrański, Michał and de Nijs, Giel and Boncz, Peter},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2903742},
url = {https://dl.acm.org/doi/10.1145/2882903.2903742},
year = {2016}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,312 | Hybrid Transactional/Analytical Processing: A Survey | 2017 | SIGMOD | 0.00011193166 |
| 2,926 | Distributed Join Algorithms on Thousands of Cores | 2017 | VLDB | 7.9549783e-05 |
| 7,780 | Petabyte-Scale Row-Level Operations in Data Lakehouses | 2024 | VLDB | 5.5457298e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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