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TAOBench: An End-to-End Benchmark for Social Network Workloads

Summary: TAOBench: end-to-end benchmark for social network workloads based on Meta production traffic, capturing realistic request patterns and emergent behavior. Open-source workload configurations, validated against production, evaluated on five distributed DBMS to reveal tradeoffs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12883
Venue
VLDB
Year
2022
Pagerank
6.4081254e-05
Overall Rank
4,996 | 65.73%
DOI
10.14778/3538598.3538616

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{cheng_vldb22,
        title = {{TAOBench: An End-to-End Benchmark for Social Network Workloads}},
        author = {Cheng, Audrey and Shi, Xiao and Kabcenell, Aaron and Lawande, Shilpa and Qadeer, Hamza and Chan, Jason and Tin, Harrison and Zhao, Ryan and Bailis, Peter and Balakrishnan, Mahesh and Bronson, Nathan and Crooks, Natacha and Stoica, Ion},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {9},
        pages = {1965--1977},
        doi = {10.14778/3538598.3538616},
        url = {https://doi.org/10.14778/3538598.3538616},
        year = {2022}
}

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