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Introducing a Query Acceleration Path for Analytics in SQLite3

Summary: Introduce SQLite3/HE: an alternative execution path and complementary storage layer that converts SQLite into a hybrid row+columnar engine. Delivers 100x–1000x analytical-query speedups while preserving transactional performance and drop-in compatibility. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
459
Venue
CIDR
Year
2022
Pagerank
5.2676282e-05
Overall Rank
9,443 | 35.22%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{prammer_cidr22,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '22},
        title = {{Introducing a Query Acceleration Path for Analytics in SQLite3}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Prammer, Martin and Rajesh, Suryadev Sahadevan and Chen, Junda and Patel, Jignesh M.},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
5,284 SQLite: Past, Present, and Future 2022 VLDB 6.2827906e-05
6,314 YeSQL: "You extend SQL" with Rich and Highly Performant User-Defined Functions in Relational Databases 2022 VLDB 5.9157364e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
12 C-Store: A Column-oriented DBMS 2005 VLDB 0.00069513174
103 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00034161428
1,312 Hybrid Transactional/Analytical Processing: A Survey 2017 SIGMOD 0.00011193166
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