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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
- 7494
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,182 | 29.24%
- 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 |
0.00040580118 |
| 608 |
Monkey: Optimal Navigable Key-Value Store |
2017 |
SIGMOD |
0.00019233548 |
| 914 |
Socrates: The New SQL Server in the Cloud |
2019 |
SIGMOD |
0.00015370799 |
| 1,169 |
SuRF: Practical Range Query Filtering with Fast Succinct Tries |
2018 |
SIGMOD |
0.00013530267 |
| 2,112 |
The Log-Structured Merge-Bush & the Wacky Continuum |
2019 |
SIGMOD |
9.5244583e-05 |
| 2,337 |
PolarDB Serverless: A Cloud Native Database for Disaggregated Data Centers |
2021 |
SIGMOD |
9.0092781e-05 |
| 2,376 |
Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless |
2022 |
VLDB |
8.9367999e-05 |
| 2,606 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
8.4621503e-05 |
| 2,797 |
Chucky: A Succinct Cuckoo Filter for LSM-Tree |
2021 |
SIGMOD |
8.1116755e-05 |
| 3,545 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
6.9831585e-05 |
| 3,970 |
Spooky: Granulating LSM-Tree Compactions Correctly |
2022 |
VLDB |
6.5756727e-05 |
| 4,659 |
Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store |
2021 |
SIGMOD |
6.0076537e-05 |
| 5,313 |
Key-Value Storage Engines |
2020 |
SIGMOD |
5.5711707e-05 |
| 5,712 |
Resource Management in Aurora Serverless |
2024 |
VLDB |
5.3596268e-05 |
| 5,801 |
Dissecting, Designing, and Optimizing LSM-based Data Stores |
2022 |
SIGMOD |
5.3217858e-05 |
| 5,920 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2686888e-05 |
| 6,066 |
Flexible Resource Allocation for Relational Database-as-a-Service |
2023 |
VLDB |
5.225259e-05 |
| 6,117 |
Compactionary: A Dictionary for LSM Compactions |
2022 |
SIGMOD |
5.1992629e-05 |
| 6,702 |
Tenant Placement in Over-subscribed Database-as-a-Service Clusters |
2022 |
VLDB |
4.9518701e-05 |
| 7,291 |
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities |
2022 |
SIGMOD |
4.7677422e-05 |
| 8,150 |
Cloud Databases: New Techniques, Challenges, and Opportunities |
2022 |
VLDB |
4.5714701e-05 |
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CloudJump: Optimizing Cloud Databases for Cloud Storages |
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VLDB |
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