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Towards Functional Decomposition of Storage Formats

Summary: Shows that tying compression blocks to row‑skipping partitions in columnar formats forces a compressibility vs scan-performance tradeoff; proposes splitting into a storage layer + Search Acceleration Layer (SAL). Finds SALs benefit from fine-grained partitions (~10–100 rows), with optimal size varying by metadata, data, and query, enabling independent tuning and improved tradeoffs. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
544
Venue
CIDR
Year
2025
Pagerank
5.2110542e-05
Overall Rank
9,836 | 32.52%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{prammer_cidr25,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '25},
        title = {{Towards Functional Decomposition of Storage Formats}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Prammer, Martin and Zeng, Xinyu and Meng, Ruijun and McKinney, Wes and Zhang, Huanchen and Pavlo, Andrew and Patel, Jignesh M.},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
9,277 F3: The Open-Source Data File Format for the Future 2026 SIGMOD 5.2937431e-05
10,057 AnyBlox: A Framework for Self-Decoding Datasets 2025 VLDB 5.1664022e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

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