| 1 |
Access Path Selection in a Relational Database Management System |
1979 |
SIGMOD |
0.0040449103 |
| 102 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
0.00049545203 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036721403 |
| 281 |
LinkBench: a Database Benchmark Based on the Facebook Social Graph |
2013 |
SIGMOD |
0.0002906793 |
| 359 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.0002592783 |
| 408 |
Database Cracking |
2007 |
CIDR |
0.00023953844 |
| 454 |
An Overview of Query Optimization in Relational Systems |
1998 |
PODS |
0.00022734812 |
| 609 |
Monkey: Optimal Navigable Key-Value Store |
2017 |
SIGMOD |
0.0001923446 |
| 801 |
SageDB: A Learned Database System |
2019 |
CIDR |
0.00016505496 |
| 899 |
Faster: A Concurrent Key-Value Store with In-Place Updates |
2018 |
SIGMOD |
0.00015509287 |
| 2,047 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
9.6920209e-05 |
| 2,130 |
SQLGraph: An Efficient Relational-Based Property Graph Store |
2015 |
SIGMOD |
9.4798556e-05 |
| 2,157 |
The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models |
2018 |
SIGMOD |
9.416022e-05 |
| 2,606 |
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn |
2019 |
CIDR |
8.4645832e-05 |
| 2,972 |
ForkBase: An Efficient Storage Engine for Blockchain and Forkable Applications |
2018 |
VLDB |
7.79259e-05 |
| 3,269 |
iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases |
2019 |
VLDB |
7.2998062e-05 |
| 3,386 |
Lethe: A Tunable Delete-Aware LSM Engine |
2020 |
SIGMOD |
7.1577103e-05 |
| 3,544 |
Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores |
2020 |
SIGMOD |
6.9898874e-05 |
| 3,659 |
Autoscaling Tiered Cloud Storage in Anna |
2019 |
VLDB |
6.8696023e-05 |
| 3,753 |
Choosing A Cloud DBMS: Architectures and Tradeoffs |
2019 |
VLDB |
6.7871241e-05 |
| 3,793 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
6.7617833e-05 |
| 4,161 |
Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe? |
2017 |
SIGMOD |
6.3938006e-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 |
| 5,356 |
LogKV: Exploiting Key-Value Stores for Event Log Processing |
2013 |
CIDR |
5.5509715e-05 |
| 5,835 |
Order-Preserving Key Compression for In-Memory Search Trees |
2020 |
SIGMOD |
5.30905e-05 |
| 6,456 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
5.0564619e-05 |
| 7,343 |
LSM-Trees and B-Trees: The Best of Both Worlds |
2019 |
SIGMOD |
4.7568442e-05 |
| 7,996 |
nKV in Action: Accelerating KV-Stores on Native Computational Storage with Near-Data Processing |
2020 |
VLDB |
4.6109657e-05 |