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Clydesdale: Structured Data Processing on Hadoop

Summary: Clydesdale, a Hadoop-based prototype for structured data processing, achieves major performance gains without changing MapReduce. By fusing DB techniques with Hadoop and exposing ClyQL, a Scala DSL for star-joins, it delivers ~38x faster star-schema workloads than Hive. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4649
Venue
SIGMOD
Year
2012
Pagerank
5.9458654e-05
Overall Rank
6,199 | 57.48%
DOI
10.1145/2213836.2213938

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{balmin_sigmod12,
        title = {{Clydesdale: Structured Data Processing on Hadoop}},
        author = {Balmin, Andrey and Kaldewey, Tim and Tata, Sandeep},
        series = {{SIGMOD} '12},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2213836.2213938},
        url = {https://dl.acm.org/doi/10.1145/2213836.2213938},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
4,230 Can the Elephants Handle the NoSQL Onslaught? 2012 VLDB 6.8178353e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

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

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