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Building Stateless Serverless Vector DBs via Block-based Data Partitioning

Summary: First experimental comparison of data partitioning for stateless FaaS vector DBs, showing clustering-based partitions fail on dynamic/bursty datasets due to complexity and load‑imbalance. Block-based partitioning yields up to 5.8× faster partitioning, ~63% lower costs and Milvus-comparable recall, enabling cost-efficient serverless vector DBs for sparse workloads. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7555
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,350 | 28.99%
DOI
10.1145/3769769

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BibTeX Citation

@inproceedings{barcelonapons_sigmod26,
        title = {{Building Stateless Serverless Vector DBs via Block-based Data Partitioning}},
        author = {Barcelona-Pons, Daniel and Gracia-Tinedo, Raúl and Cañadilla-Domingo, Albert and Roca-Canals, Xavier and García-López, Pedro},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3769769},
        url = {https://dl.acm.org/doi/10.1145/3769769},
        year = {2026}
}

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