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Schema-Agnostic Indexing with Azure DocumentDB

Summary: Presents DocumentDB’s schema-agnostic, automatic indexing for JSON at Internet scale, eliminating secondary-index administration. Its distinctive design delivers real-time-consistent queries under intense updates while preserving predictable performance and tenant isolation under frugal resource budgets. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11233
Venue
VLDB
Year
2015
Pagerank
7.4241655e-05
Overall Rank
3,424 | 76.51%
DOI
10.14778/2824032.2824065

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shukla_vldb15,
        title = {{Schema-Agnostic Indexing with Azure DocumentDB}},
        author = {Shukla, Dharma and Thota, Shireesh and Raman, Karthik and Gajendran, Madhan and Shah, Ankur and Ziuzin, Sergii and Sundaram, Krishnan and Guajardo, Miguel Gonzalez and Wawrzyniak, Anna and Boshra, Samer and Ferreira, Renato and Nassar, Mohamed and Koltachev, Michael and Huang, Ji and Sengupta, Sudipta and Levandoski, Justin and Lomet, David},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {12},
        pages = {1668--1679},
        doi = {10.14778/2824032.2824065},
        url = {https://doi.org/10.14778/2824032.2824065},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

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

Rank Cited Paper Year Venue Pagerank
1,461 LLAMA: A Cache/Storage Subsystem for Modern Hardware 2013 VLDB 0.00010703712
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