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)
Incoming Non-self Citations Over Time
Authors
- 1. Volker Markl
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,807 | Resource Elasticity for Large-Scale Machine Learning | 2015 | SIGMOD | 5.9045148e-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 |
|---|---|---|---|---|
| 1,797 | epiC: an Extensible and Scalable System for Processing Big Data | 2014 | VLDB | 0.00010502488 |
| 2,179 | Spinning Fast Iterative Data Flows | 2012 | VLDB | 9.3632007e-05 |
| 4,496 | ASTERIX: An Open Source System for "Big Data" Management and Analysis (Demo) | 2012 | VLDB | 6.1357056e-05 |
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