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

Summary: Argues that big-data systems’ lack of data independence and declarative specifications forces data scientists to hand-tune analyses for data and execution environments, hindering broad adoption. Calls for declarative analytics abstractions to restore database-style usability. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: h4f975d069b9a7688
Venue: VLDB
Year: 2014
Pagerank: 5.0982945e-05
Overall Rank: 9,994 | 32.83%
DOI: 10.14778/2733004.2733075
PDF: Download (CC BY-NC-ND 3.0)

Incoming Non-self Citations Over Time

Authors

1. Volker Markl (Technical University of Berlin)

BibTeX Citation

@article{markl_vldb14,
        title = {{Breaking the Chains: On Declarative Data Analysis and Data Independence in the Big Data Era}},
        author = {Markl, Volker},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {13},
        pages = {1730},
        doi = {10.14778/2733004.2733075},
        url = {https://doi.org/10.14778/2733004.2733075},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,117	Resource Elasticity for Large-Scale Machine Learning	2015	SIGMOD	6.7929814e-05

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
2,228	Spinning Fast Iterative Data Flows	2012	VLDB	8.7996087e-05
2,411	epiC: an Extensible and Scalable System for Processing Big Data	2014	VLDB	8.5073756e-05
4,880	ASTERIX: An Open Source System for "Big Data" Management and Analysis (Demo)	2012	VLDB	6.3689373e-05

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