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Scalar DL: Scalable and Practical Byzantine Fault Detection for Transactional Database Systems

Summary: Scalar DL is a db-agnostic BFD middleware for transactional DBs; two replicas ensure detection if one is honest. It runs conflict-free transactions in parallel with a correctness guarantee, beating prior BFD by 3.5–10.6× and nearlinear scalability. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12829
Venue
VLDB
Year
2022
Pagerank
5.484341e-05
Overall Rank
8,111 | 44.36%
DOI
10.14778/3523210.3523212

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{yamada_vldb22,
        title = {{Scalar DL: Scalable and Practical Byzantine Fault Detection for Transactional Database Systems}},
        author = {Yamada, Hiroyuki and Nemoto, Jun},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {7},
        pages = {1324--1336},
        doi = {10.14778/3523210.3523212},
        url = {https://doi.org/10.14778/3523210.3523212},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
8,406 ScalarDB: Universal Transaction Manager for Polystores 2023 VLDB 5.4314245e-05
10,356 DAG of DAGs: Order-Fairness Made Practical 2026 SIGMOD 5.093636e-05
10,988 Pistis: A Decentralized Knowledge Graph Platform Enabling Ownership-Preserving SPARQL Querying 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

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