The Drill Down Benchmark

Summary: Introduces the Drill Down (DD) Benchmark, targeting data-mining query workloads that OLAP benchmarks miss. Derived from Data Surveyor tasks across DBMS backends, it evaluates practical drill-down performance and reports initial Monet versus relational-DBMS results. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 8716
Venue: VLDB
Year: 1998
Pagerank: 5.7989922e-05
Overall Rank: 6,695 | 54.07%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Peter A. Boncz (Data Distilleries B.V.)
2. Tim Rühl (Data Distilleries B.V.)
3. Fred Kwakkel (Data Distilleries B.V.)

BibTeX Citation

@article{boncz_vldb98,
        title = {{The Drill Down Benchmark}},
        author = {Boncz, Peter A. and Rühl, Tim and Kwakkel, Fred},
        journal = {PVLDB},
        series = {{VLDB} '98},
        pages = {628},
        year = {1998}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,875	Cracking the Database Store	2005	CIDR	7.0543045e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
27	Fast Algorithms for Mining Association Rules	1994	VLDB	0.00052254947
74	Cache Conscious Algorithms for Relational Query Processing	1994	VLDB	0.00037331466

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