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Making LSM-Tree-based Key-Value Store Practical and Efficient for Multi-Tenant Serverless Cloud Databases
Summary: FlexEngine makes LSM-tree storage practical for multi-tenant serverless cloud DBs by balancing tenant SLAs against aggressive storage-bandwidth oversubscription. Key ideas: two-level I/O admission control plus two-stage compaction deferral on RocksDB, boosting cost-efficiency without sacrificing consistency.
(summarized by gpt-5-mini on Apr 11 2026)
- Paper ID
- 7493
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,182 | 29.17%
- DOI
-
10.1145/3786667
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 21 of 21 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 156 |
Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases |
2017 |
SIGMOD |
0.00040504295 |
| 609 |
Monkey: Optimal Navigable Key-Value Store |
2017 |
SIGMOD |
0.0001923446 |
| 918 |
Socrates: The New SQL Server in the Cloud |
2019 |
SIGMOD |
0.00015350181 |
| 1,169 |
SuRF: Practical Range Query Filtering with Fast Succinct Tries |
2018 |
SIGMOD |
0.00013536447 |
| 2,109 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
9.5318694e-05 |
| 2,358 |
PolarDB Serverless: A Cloud Native Database for Disaggregated Data Centers |
2021 |
SIGMOD |
8.9617346e-05 |
| 2,375 |
Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless |
2022 |
VLDB |
8.9452359e-05 |
| 2,606 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
8.4645832e-05 |
| 2,798 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
8.1080111e-05 |
| 3,544 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
6.9898874e-05 |
| 3,965 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
6.5820028e-05 |
| 4,662 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
6.013415e-05 |
| 5,308 |
Key-Value Storage Engines |
2020 |
SIGMOD |
5.576303e-05 |
| 5,701 |
Resource Management in Aurora Serverless |
2024 |
VLDB |
5.3647775e-05 |
| 5,791 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
5.3268999e-05 |
| 5,918 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2737135e-05 |
| 6,062 |
Flexible Resource Allocation for Relational Database-as-a-Service |
2023 |
VLDB |
5.2302798e-05 |
| 6,113 |
Compactionary: A Dictionary for LSM Compactions |
2022 |
SIGMOD |
5.20426e-05 |
| 6,699 |
Tenant Placement in Over-subscribed Database-as-a-Service Clusters |
2022 |
VLDB |
4.9566258e-05 |
| 7,296 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
4.7723197e-05 |
| 7,543 |
Cloud Databases: New Techniques, Challenges, and Opportunities |
2022 |
VLDB |
4.715241e-05 |
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| 1,366 |
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CloudJump: Optimizing Cloud Databases for Cloud Storages |
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VLDB |
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