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Breaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era

Summary: Big data lacks data independence and declarative specification, curbing broad adoption to IT-savvy firms. The paper argues for embedding declarative data-analysis and data-independence concepts into big-data stacks to ease tuning, enable schema-independence, and broaden access for data scientists. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10866
Venue
VLDB
Year
2014
Pagerank
4.3082114e-05
Overall Rank
9,666 | 32.76%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
4,802 Resource Elasticity for Large-Scale Machine Learning 2015 SIGMOD 5.9114415e-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
1,800 epiC: an Extensible and Scalable System for Processing Big Data 2014 VLDB 0.00010512649
2,172 Spinning Fast Iterative Data Flows 2012 VLDB 9.3706587e-05
4,493 ASTERIX: An Open Source System for "Big Data" Management and Analysis (Demo) 2012 VLDB 6.141595e-05
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