PASE: PostgreSQL Ultra-High-Dimensional Approximate Nearest Neighbor Search Extension
Summary: Extends PostgreSQL with a novel index-type for ultra-high-dim approximate NN search, enabling composite vector queries and seamless data integration. PASE offers two fast NNS algorithms in a unified PostgreSQL extension, enabling other NNS methods and proving efficiency on large datasets. (summarized by gpt-5-nano on Feb 09 2026)
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BibTeX Citation
@inproceedings{yang_sigmod20,
title = {{PASE: PostgreSQL Ultra-High-Dimensional Approximate Nearest Neighbor Search Extension}},
author = {Yang, Wen and Li, Tao and Fang, Gai and Wei, Hong},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3386131},
url = {https://dl.acm.org/doi/10.1145/3318464.3386131},
year = {2020}
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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 |
|---|---|---|---|---|
| 75 | Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph | 2019 | VLDB | 0.00037163157 |
| 2,030 | FREDDY: Fast Word Embeddings in Database Systems | 2018 | SIGMOD | 9.1437256e-05 |
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