RecBench: Benchmarks for Evaluating Performance of Recommender System Architectures

Summary: Defines RecBench benchmarks for evaluating DBMS-based vs hand-built recommender architectures. Evaluates MultiLens vs RecStore on MovieLens 10M and Netflix 100M, showing hand-built excels in model-building and pure recommendations, while DBMS-based shines in filtered/hybrid tasks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 10320
Venue: VLDB
Year: 2011
Pagerank: 4.1905499e-05
Overall Rank: 12,219 | 15.08%
DOI: -

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Rank	Citing Paper	Year	Venue	Pagerank

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Showing 9 of 9 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
10	Benchmarking Database Systems: A Systematic Approach	1983	VLDB	0.0012093675
53	DISCOVER: Keyword Search in Relational Databases	2002	VLDB	0.00065993143
469	On Saying "Enough Already!" in SQL	1997	SIGMOD	0.00022397468
926	Requirements for Science Data Bases and SciDB	2009	CIDR	0.00015237787
1,149	A Comprehensive XQuery to SQL Translation using Dynamic Interval Encoding	2003	SIGMOD	0.00013649094
1,968	A Methodology for Database System Performance Evaluation	1984	SIGMOD	9.9099939e-05
2,066	System RX: One Part Relational, One Part XML	2005	SIGMOD	9.64571e-05
2,982	FlexRecs: Expressing and Combining Flexible Recommendations	2009	SIGMOD	7.7771174e-05
4,534	LegoDB: Customizing Relational Storage for XML Documents	2002	VLDB	6.1014581e-05

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