Cost-Effective, Low Latency Vector Search with Azure Cosmos DB

Summary: Embed DiskANN in Cosmos DB: one per-partition vector index in existing index trees, <20ms queries on 10M vectors, stable recall under updates. Shows ~43x/12x lower query cost vs Pinecone/Zilliz and automatic partitioning to scale to billions—argues for DB-integrated vectors. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14116
Venue: VLDB
Year: 2025
Pagerank: 4.3341665e-05
Overall Rank: 9,480 | 34.05%
DOI: 10.14778/3750601.3750635

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,224	SVFusion: A CPU-GPU Co-Processing Architecture for Large-Scale Real-Time Vector Search	2026	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
212	Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph	2019	VLDB	0.00033913475
736	AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data	2020	VLDB	0.00017447617
3,400	ELPIS: Graph-Based Similarity Search for Scalable Data Science	2023	VLDB	7.1405533e-05
3,680	SingleStore-V: An Integrated Vector Database System in SingleStore	2024	VLDB	6.8496415e-05
3,792	Schema-Agnostic Indexing with Azure DocumentDB	2015	VLDB	6.7618051e-05

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