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Excalibur: A Virtual Machine for Adaptive Fine-grained JIT-Compiled Query Execution based on VOILA

Summary: Excalibur is a VOILA-based VM that adaptively swaps fine-grained query-pipeline tactics via JIT compilation, spanning vectorized and specialized execution flavors. It frames tactic selection as a multi-armed bandit, outperforming Umbra by up to 1.8×. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
he8a20c435820c517
Venue
VLDB
Year
2023
Pagerank
5.4141361e-05
Overall Rank
7,966 | 46.46%
DOI
10.14778/3574245.3574266
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{gubner_vldb23,
        title = {{Excalibur: A Virtual Machine for Adaptive Fine-grained JIT-Compiled Query Execution based on VOILA}},
        author = {Gubner, Tim and Boncz, Peter},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {4},
        pages = {829--841},
        doi = {10.14778/3574245.3574266},
        url = {https://doi.org/10.14778/3574245.3574266},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
14 MonetDB/X100: Hyper-Pipelining Query Execution 2005 CIDR 0.00064013679
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061067652
21 Efficiently Compiling Efficient Query Plans for Modern Hardware 2011 VLDB 0.00056835296
23 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00055384955
163 DB2 with BLU Acceleration: So Much More than Just a Column Store 2013 VLDB 0.00027480091
196 Grammar-like Functional Rules for Representing Query Optimization Alternatives 1988 SIGMOD 0.00025616489
215 Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age 2014 SIGMOD 0.00024589307
373 Umbra: A Disk-Based System with In-Memory Performance 2020 CIDR 0.00019705706
605 Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask 2018 VLDB 0.00015640305
681 Amazon Redshift Re-invented 2022 SIGMOD 0.0001482366
907 Data Blocks: Hybrid OLTP and OLAP on Compressed Storage using both Vectorization and Compilation 2016 SIGMOD 0.00013157412
963 Memory-Efficient Hash Joins 2015 VLDB 0.00012815832
1,487 Photon: A Fast Query Engine for Lakehouse Systems 2022 SIGMOD 0.00010516813
3,043 Fast, Randomized Join-Order Selection—Why Use Transformations? 1994 VLDB 7.7178769e-05
3,102 Micro Adaptivity in Vectorwise 2013 SIGMOD 7.6469535e-05
3,986 Designing an Open Framework for Query Optimization and Compilation 2022 VLDB 6.8697828e-05
4,796 Permutable Compiled Queries: Dynamically Adapting Compiled Queries without Recompiling 2021 VLDB 6.409726e-05
5,545 Charting the Design Space of Query Execution using VOILA 2021 VLDB 6.0860849e-05
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