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)
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Authors
- 1. Hokeun Cha
- 2. Xiangpeng Hao
- 3. Tianzheng Wang
- 4. Huanchen Zhang
- 5. Aditya Akella
- 6. Xiangyao Yu
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| Rank | Citing Paper | Year | Venue | Pagerank |
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| 5,060 | The Art of Latency Hiding in Modern Database Engines | 2024 | VLDB | 5.7175345e-05 |
| 7,152 | Bf-Tree: A Modern Read-Write-Optimized Concurrent Larger-Than-Memory Range Index | 2024 | VLDB | 4.8126591e-05 |
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