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FITing-Tree: A Data-aware Index Structure
Summary: FITing-Tree presents a data-aware index that uses piecewise-linear approximations bounded by a tunable error. A cost model selects the error to balance lookup latency and storage, delivering near full-index performance with orders of magnitude less memory on real datasets.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h9761bd39cb86219d
Venue
SIGMOD
Year
2019
Pagerank
0.00014030069
Overall Rank
779 | 94.77%
DOI
10.1145/3299869.3319860
Incoming Non-self Citations Over Time
BibTeX Citation
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@inproceedings{galakatos_sigmod19,
title = {{FITing-Tree: A Data-aware Index Structure}},
author = {Galakatos, Alex and Markovitch, Michael and Binnig, Carsten and Fonseca, Rodrigo and Kraska, Tim},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3319860},
url = {https://dl.acm.org/doi/10.1145/3299869.3319860},
year = {2019}
}
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