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Abstraction without regret in data management systems

Summary: Argues data management research produces short-lived, recipe-like contributions instead of timeless abstractions and design patterns. Calls for extracting first principles (e.g., locality, out-of-core) to enable enduring, reusable abstractions and clearer crediting. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
192
Venue
CIDR
Year
2013
Pagerank
4.6815729e-05
Overall Rank
7,676 | 46.60%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
704 Building Efficient Query Engines in a High-Level Language 2014 VLDB 0.00017900583
2,383 How to Architect a Query Compiler 2016 SIGMOD 8.9294108e-05
3,548 Adaptive Query Processing on RAW Data 2014 VLDB 6.9859242e-05
7,470 The Case for Deep Query Optimisation 2020 CIDR 4.7201897e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

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