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Petabyte Scale Databases and Storage Systems at Facebook

Summary: Facebook's petabyte-scale data stack: sharded MySQL+Memcache for real-time access, TAO for geo consistency, Haystack for billions of photos, Hadoop/HBase for analytics. Examines workload-driven choices, ACID needs, and graph-relational mapping for geo deployments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4708
Venue
SIGMOD
Year
2013
Pagerank
5.8056697e-05
Overall Rank
6,676 | 54.20%
DOI
10.1145/2463676.2463713

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{borthakur_sigmod13,
        title = {{Petabyte Scale Databases and Storage Systems at Facebook}},
        author = {Borthakur, Dhruba},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2463713},
        url = {https://dl.acm.org/doi/10.1145/2463676.2463713},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
1,492 BF-Tree: Approximate Tree Indexing 2014 VLDB 0.00010588267
2,233 FINEdex: A Fine-grained Learned Index Scheme for Scalable and Concurrent Memory Systems 2022 VLDB 8.8968964e-05
8,056 Sieve: A Learned Data-Skipping Index for Data Analytics 2023 VLDB 5.4983582e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank Cited Paper Year Venue Pagerank
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