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FAD.js: Fast JSON Data Access Using JIT-based Speculative Optimizations

Summary: FAD.js accelerates JSON access with speculative JIT compilation and selective field retrieval, avoiding unnecessary parsing/serialization work. Compared with state-of-the-art libraries, it delivers up to 2.7× faster encoding and 9.9× faster decoding. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11647
Venue
VLDB
Year
2017
Pagerank
6.3870952e-05
Overall Rank
5,048 | 65.37%
DOI
10.14778/3137765.3137782

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{bonetta_vldb17,
        title = {{FAD.js: Fast JSON Data Access Using JIT-based Speculative Optimizations}},
        author = {Bonetta, Daniele and Brantner, Matthias},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {12},
        doi = {10.14778/3137765.3137782},
        url = {https://doi.org/10.14778/3137765.3137782},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

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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
1,155 Projecting XML Documents 2003 VLDB 0.00011933524
4,206 NoDB in Action: Adaptive Query Processing on Raw Data 2012 VLDB 6.8334568e-05
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