RABIT: Efficient Range Queries with Bitmap Indexing
Summary: RABIT generalizes bitmap indexes with Group Encoding and density-aware bitvector merging (choose compressed/decompressed, SIMD) to support fast range queries and low-latency updates for any-cardinality attributes. A multi-layer update design provides lightweight MV snapshots and index-only scans with single-version bitvectors, delivering up to 2.2× faster RQs, 530× faster updates, 118× smaller index vs trees and 14.8× TPC‑H speedups. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Junchang Wang (Nanjing University)
- 2. Fu Xiao (Nanjing University)
- 3. Manos Athanassoulis (Boston University)
BibTeX Citation
@inproceedings{wang_sigmod26,
title = {{RABIT: Efficient Range Queries with Bitmap Indexing}},
author = {Wang, Junchang and Xiao, Fu and Athanassoulis, Manos},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3769819},
url = {https://dl.acm.org/doi/10.1145/3769819},
year = {2026}
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