The HANA Native Query Engine for Lakehouse Systems
Summary: Adapts SAP HANA Cloud into a SQL-on-Files engine for scalable analytics directly over remote Parquet/Iceberg/Delta lakehouse data. Its architecture, optimizer, and caching favor direct access over pushdown, yielding superior performance on complex warehouse workloads. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Daniel Ritter (SAP)
- 2. Mihnea Andrei (SAP)
- 3. Sukhyeun Cho (SAP)
- 4. Maik Görgens (SAP)
- 5. Taehyung Lee (SAP)
- 6. Norman May (SAP)
- 7. Amit Pathak (SAP)
- 8. Paul R. Willems (SAP)
BibTeX Citation
@article{ritter_vldb25,
title = {{The HANA Native Query Engine for Lakehouse Systems}},
author = {Ritter, Daniel and Andrei, Mihnea and Cho, Sukhyeun and Görgens, Maik and Lee, Taehyung and May, Norman and Pathak, Amit and Willems, Paul R.},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {12},
pages = {4831--4845},
doi = {10.14778/3750601.3750608},
url = {https://doi.org/10.14778/3750601.3750608},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,971 | Overlay Bitmap Encoding for Efficient Consumption of Apache Parquet Files | 2026 | VLDB | 4.9605343e-05 |
| 10,985 | Reaching the Pinnacle of TPC-DS: Co-design of Architecture, Executor, and Storage in TDSQL | 2026 | VLDB | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 36 of 36 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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