Chipmink: Efficient Delta Identification for Massive Object Graphs

Summary: Chipmink partitions massive object graphs into dynamic 'pods' to emulate a buffer manager and isolate dirty objects across memory, shared-memory, GPUs, and remote devices. Pods minimize expected persistence cost via sizes and references, enabling partial persistence with up to 36.5× less storage and 12.4× faster persistence than baselines. (summarized by gpt-5-mini on Mar 13 2026)

Paper ID: 14344
Venue: VLDB
Year: 2026
Pagerank: 4.1945683e-05
Overall Rank: 10,302 | 28.34%
DOI: 10.14778/3785297.3785303

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Rank	Citing Paper	Year	Venue	Pagerank

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Showing 11 of 11 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
85	Making Smalltalk a Database System	1984	SIGMOD	0.00053428612
1,698	Query Processing in the ObjectStore Database System	1992	SIGMOD	0.00010869294
2,494	Streaming Graph Partitioning: An Experimental Study	2018	VLDB	8.6508229e-05
3,752	Computing Graph Edit Distance via Neural Graph Matching	2023	VLDB	6.7879009e-05
7,735	AeonG: An Efficient Built-in Temporal Support in Graph Databases	2024	VLDB	4.6644355e-05
9,095	AirIndex: Versatile Index Tuning Through Data and Storage	2023	SIGMOD	4.3975034e-05
9,912	ElasticNotebook: Enabling Live Migration for Computational Notebooks	2024	VLDB	4.2565279e-05
10,286	QStore: Quantization-Aware Compressed Model Storage	2026	VLDB	4.1945683e-05
10,434	Demo of Kishu: Time-Traveling for Computational Notebooks	2025	SIGMOD	4.1945683e-05
10,761	SIEVE: Effective Filtered Vector Search with Collection of Indexes	2025	VLDB	4.1945683e-05
10,888	Kishu: Time-Traveling for Computational Notebooks	2025	VLDB	4.1945683e-05

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