A Database System with Amnesia

Summary: Introduces "data rotting": a mostly‑knobless DBMS that semi‑autonomously forgets tuples (marks them inactive) to trade retention for bounded cost and interactive response. Empirical study of amnesia scenarios and implementation strategies to guide retrofitting engines with built‑in forgetting policies. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 306
Venue: CIDR
Year: 2017
Pagerank: 5.1692384e-05
Overall Rank: 6,178 | 57.03%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Martin Kersten
2. Lefteris Sidirourgos

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,501	DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models	2019	SIGMOD	8.6453446e-05
2,606	Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn	2019	CIDR	8.4645832e-05
6,456	From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems	2019	SIGMOD	5.0564619e-05
10,116	Stochastic Submodular Data Forgetting	2026	SIGMOD	4.1945683e-05
10,838	New Trends in Data Forgetting for Sustainable Data Management	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
982	Anti-Caching: A New Approach to Database Management System Architecture	2013	VLDB	0.00014872253
1,335	ICICLES: Self-tuning Samples for Approximate Query Answering	2000	VLDB	0.00012502131
1,909	SciBORQ: Scientific data management with Bounds On Runtime and Quality	2011	CIDR	0.00010121304
6,649	Big Data Space Fungus	2015	CIDR	4.9768878e-05
11,897	Capturing the Laws of (Data) Nature	2015	CIDR	4.1945683e-05

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