Benchmarking Adaptive Multidimensional Indices
Summary: Benchmark comparing multidimensional adaptive-indexing methods across data types, distributions, sizes and workloads to expose relative strengths and failure modes. Proposes efficiency-enhancing tweaks and practical guidance for choosing/adapting methods in exploratory or evolving-data scenarios. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Konstantinos Lampropoulos (Aarhus University; University of Ioannina)
- 2. Fatemeh Zardbani (Aarhus University)
- 3. Nikos Mamoulis (Athena Research Center; University of Ioannina)
- 4. Panagiotis Karras (Aarhus University; University of Copenhagen)
BibTeX Citation
@article{lampropoulos_vldb25,
title = {{Benchmarking Adaptive Multidimensional Indices}},
author = {Lampropoulos, Konstantinos and Zardbani, Fatemeh and Mamoulis, Nikos and Karras, Panagiotis},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {11},
pages = {4505--4517},
doi = {10.14778/3749646.3749709},
url = {https://doi.org/10.14778/3749646.3749709},
year = {2025}
}
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