Evolution of a Compiling Query Engine
Summary: Evolution of a compiling query engine based on data-centric code generation, delivering compact, efficient query code. Also discusses low-latency compilation, multi-threading, and the production challenges needed to bring compiling systems to scale. (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_vldb21,
title = {{Evolution of a Compiling Query Engine}},
author = {Neumann, Thomas},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {3207--3210},
doi = {10.14778/3476311.3476410},
url = {https://doi.org/10.14778/3476311.3476410},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,066 | The LDBC Social Network Benchmark: Business Intelligence Workload | 2023 | VLDB | 7.6714389e-05 |
| 6,688 | Composable Data Management: An Execution Overview | 2024 | VLDB | 5.6925768e-05 |
| 7,487 | Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code | 2024 | VLDB | 5.4995746e-05 |
| 9,729 | The UDFBench Benchmark for General-purpose UDF Queries | 2025 | VLDB | 5.1202393e-05 |
| 11,724 | mutable: A Modern DBMS for Research and Fast Prototyping | 2023 | CIDR | 4.9605343e-05 |
| 11,829 | Big Data Analytic Toolkit: A general-purpose, modular, and heterogeneous acceleration toolkit for data analytical engines | 2023 | VLDB | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 10 | 1,756 | How to Architect a Query Compiler | 2016 | SIGMOD |