Efficient Vector Index Merging in Vector Databases
Summary: HNSW-Merger: efficient merging of vector indexes in vector DBs, targeting a key bottleneck in index construction/updates. Two-stage search-based merge exploits existing proximity info via forward HNSW search + lazy backward direct-connect, with multicore/memory optimizations and multi-index support. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Chenzhe Jin (Purdue University)
- 2. Yunan Zhang (Purdue University)
- 3. Jiayi Liu (Purdue University)
- 4. Jianguo Wang (Purdue University)
BibTeX Citation
@inproceedings{jin_sigmod26,
title = {{Efficient Vector Index Merging in Vector Databases}},
author = {Jin, Chenzhe and Zhang, Yunan and Liu, Jiayi and Wang, Jianguo},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786645},
url = {https://dl.acm.org/doi/10.1145/3786645},
year = {2026}
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