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Solving Big Data Challenges for Enterprise Application Performance Management

Summary: Industry-driven evaluation of six open-source key-value stores for high-rate, long-retention application-performance monitoring data and fresh infrastructure views. Compares realistic APM and related workloads, exposing performance tradeoffs plus deployment and configuration lessons. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10598
Venue
VLDB
Year
2012
Pagerank
6.9864509e-05
Overall Rank
3,963 | 72.82%
DOI
10.14778/2367502.2367512

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{rabl_vldb12,
        title = {{Solving Big Data Challenges for Enterprise Application Performance Management}},
        author = {Rabl, Tilmann and Sadoghi, Mohammad and Jacobsen, Hans-Arno and Gómez-Villamor, Sergio and Muntés-Mulero, Victor and Mankovskii, Serge},
        journal = {PVLDB},
        series = {{VLDB} '12},
        volume = {5},
        number = {12},
        doi = {10.14778/2367502.2367512},
        url = {https://doi.org/10.14778/2367502.2367512},
        year = {2012}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
47 PNUTS: Yahoo!'s Hosted Data Serving Platform 2008 VLDB 0.00044503718
83 H-Store: A High-Performance, Distributed Main Memory Transaction Processing System 2008 VLDB 0.00036185259
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