Database Paper Browser

Back to papers

Rumble: Data Independence for Large Messy Data Sets

Summary: Rumble delivers data independence for large, nested JSON on Spark by compiling JSONiq into an iterator tree that switches between local and distributed execution. Bridging JSON nesting with Spark primitives, it overcomes impedance mismatch, scales to terabytes, and demonstrates Codd-like independence for heterogeneous data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12569
Venue
VLDB
Year
2021
Pagerank
4.5453618e-05
Overall Rank
8,271 | 42.47%
DOI
10.14778/3436905.3436910

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Previous Page 1 / 1 Next

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.

Previous Page 1 / 1 Next

Semantically Similar Papers