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Blink-hash: An Adaptive Hybrid Index for In-Memory Time-Series Databases

Summary: Blink-hash: hybrid index enhancing B+-trees with large hash leaf nodes to randomize monotonically increasing timestamp inserts and remove hot-spot contention in in-memory time-series workloads. With median-approximation, lazy-split, and dynamic reconversion to B+-tree leaves for scans, it attains up to 91.3× higher ingestion throughput than conventional indexes while maintaining comparable scan performance. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
12990
Venue
VLDB
Year
2023
Pagerank
4.1945683e-05
Overall Rank
11,229 | 21.89%
DOI
10.14778/3583140.3583143

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Rank Citing Paper Year Venue Pagerank
5,312 The Art of Latency Hiding in Modern Database Engines 2024 VLDB 5.5734224e-05
7,154 Bf-Tree: A Modern Read-Write-Optimized Concurrent Larger-Than-Memory Range Index 2024 VLDB 4.815267e-05
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