Bringing Compiling Databases to RISC Architectures
Summary: Evaluates query-code-generation strategies for Umbra on x86-64 and AArch64, measuring compilation latency and throughput. Introduces FireARM, an AArch64 generator, showing domain-specific code lowers compilation overhead while standard infrastructures ease portability and sustain strong big-data performance. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ferdinand Gruber (Technical University of Munich)
- 2. Maximilian Bandle (Technical University of Munich)
- 3. Alexis Engelke (Technical University of Munich)
- 4. Thomas Neumann (Technical University of Munich)
- 5. Jana Giceva (Technical University of Munich)
BibTeX Citation
@article{gruber_vldb23,
title = {{Bringing Compiling Databases to RISC Architectures}},
author = {Gruber, Ferdinand and Bandle, Maximilian and Engelke, Alexis and Neumann, Thomas and Giceva, Jana},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {6},
pages = {1222--1234},
doi = {10.14778/3583140.3583142},
url = {https://doi.org/10.14778/3583140.3583142},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,443 | Analyzing Vectorized Hash Tables Across CPU Architectures | 2023 | VLDB | 5.4243766e-05 |
| 10,072 | Query Compilation Without Regrets | 2024 | SIGMOD | 5.1624689e-05 |
| 10,541 | Scalable GPU Acceleration of Scalar Functions in Analytical Databases: Compilation, Benchmarking, and Optimization | 2026 | VLDB | 5.093636e-05 |
| 11,120 | Welding Natural Language Queries to Analytics IRs with LLMs | 2024 | CIDR | 5.093636e-05 |
Previous
Page 1 / 1
Next
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.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 5,376 | Evolution of a Compiling Query Engine | 2021 | VLDB |
| 2 | 8,636 | Adaptive Code Generation for Data-Intensive Analytics | 2021 | VLDB |
| 3 | 4,215 | Designing an Open Framework for Query Optimization and Compilation | 2022 | VLDB |
| 4 | 600 | Rethinking Database System Architecture: Towards a Self-tuning RISC-style Database System | 2000 | VLDB |
| 5 | 11,708 | Low-Latency Compilation of SQL Queries to Machine Code | 2021 | VLDB |
| 6 | 23 | Efficiently Compiling Efficient Query Plans for Modern Hardware | 2011 | VLDB |
| 7 | 534 | Building Efficient Query Engines in a High-Level Language | 2014 | VLDB |
| 8 | 1,797 | How to Architect a Query Compiler | 2016 | SIGMOD |
| 9 | 9,082 | An Application-Specific Instruction Set for Accelerating Set-Oriented Database Primitives | 2014 | SIGMOD |
| 10 | 2,488 | How to Architect a Query Compiler, Revisited | 2018 | SIGMOD |