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Database Cracking

Summary: Presents database cracking: adaptive, incremental reorganization of columnar data during query execution to build partial indexes on‑the‑fly by partitioning data per predicate. Integrated into an RDBMS with minimal kernel changes, enabling self‑organizing, low‑overhead indexing that adapts to shifting workloads and influences optimizer plans. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h8fa153ccaba0a25f
Venue
CIDR
Year
2007
Pagerank
0.00023042111
Overall Rank
253 | 98.31%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{idreos_cidr07,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '07},
        title = {{Database Cracking}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Idreos, Stratos and Kersten, Martin L. and Manegold, Stefan},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 104 citing papers.

Rank Citing Paper Year Venue Pagerank
11,601 Partition, Don’t Sort! Compression Boosters for Cloud Data Ingestion Pipelines 2024 VLDB 4.9793485e-05
11,750 Cracking-Like Join for Trusted Execution Environments 2023 VLDB 4.9793485e-05
12,287 Alpine: Efficient In situ Data Exploration in the Presence of Updates 2017 SIGMOD 4.9793485e-05
12,648 No Bits Left Behind 2011 CIDR 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

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