| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 905 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423174 |
| 1,161 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013579831 |
| 1,372 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.0001233325 |
| 1,574 |
Approximate Query Processing: No Silver Bullet |
2017 |
SIGMOD |
0.00011289028 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011050093 |
| 1,699 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010848882 |
| 2,126 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.4814404e-05 |
| 2,254 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
9.1871115e-05 |
| 2,781 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1282042e-05 |
| 2,988 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
7.7752463e-05 |
| 3,516 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.018912e-05 |
| 3,644 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8842065e-05 |
| 3,781 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
6.7691344e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6056349e-05 |
| 3,992 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5519369e-05 |
| 4,020 |
Revisiting Reuse for Approximate Query Processing |
2017 |
VLDB |
6.5209063e-05 |
| 4,431 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.1870601e-05 |
| 5,022 |
Towards Distribution-aware Query Answering in Data Markets |
2022 |
VLDB |
5.7479778e-05 |
| 5,085 |
Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins |
2023 |
PODS |
5.7040225e-05 |
| 5,128 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
5.6728511e-05 |
| 5,405 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
5.5243727e-05 |
| 5,817 |
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees |
2019 |
SIGMOD |
5.3154329e-05 |
| 5,910 |
At-the-time and Back-in-time Persistent Sketches |
2021 |
SIGMOD |
5.2718714e-05 |
| 5,952 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
5.2547498e-05 |
| 5,982 |
Responsible Data Integration: Next-generation Challenges |
2022 |
SIGMOD |
5.2409386e-05 |
| 6,207 |
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration |
2021 |
SIGMOD |
5.1519085e-05 |
| 6,288 |
Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach |
2024 |
VLDB |
5.1226099e-05 |
| 6,402 |
Approximate Query Engines: Commercial Challenges and Research Opportunities |
2017 |
SIGMOD |
5.0725227e-05 |
| 6,462 |
Tailoring Data Source Distributions for Fairness-aware Data Integration |
2021 |
VLDB |
5.0479645e-05 |
| 6,481 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.039683e-05 |
| 6,705 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
4.9507418e-05 |
| 6,715 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
4.9464666e-05 |
| 6,911 |
Continuous Prefetch for Interactive Data Applications |
2020 |
VLDB |
4.8878659e-05 |
| 7,118 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
4.8204951e-05 |
| 7,246 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
4.7847433e-05 |
| 7,340 |
Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries |
2021 |
SIGMOD |
4.7526052e-05 |
| 7,450 |
Scalable Approximate Butterfly and Bi-triangle Counting for Large Bipartite Networks |
2023 |
SIGMOD |
4.7218383e-05 |
| 7,533 |
Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams |
2022 |
VLDB |
4.7134753e-05 |
| 7,571 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
4.7037322e-05 |
| 7,854 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
4.6306186e-05 |
| 8,057 |
Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines |
2024 |
VLDB |
4.5903427e-05 |
| 8,235 |
Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters |
2019 |
VLDB |
4.5481384e-05 |
| 8,606 |
ProgressiveDB – Progressive Data Analytics as a Middleware |
2019 |
VLDB |
4.4811623e-05 |
| 8,772 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
4.451034e-05 |
| 8,873 |
Privacy Amplification by Sampling under User-level Differential Privacy |
2024 |
SIGMOD |
4.4271393e-05 |
| 9,416 |
Leveraging Application Data Constraints to Optimize Database-Backed Web Applications |
2023 |
VLDB |
4.3399748e-05 |
| 9,621 |
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation |
2023 |
VLDB |
4.3125802e-05 |
| 9,653 |
Secure Sampling for Approximate Multi-party Query Processing |
2023 |
SIGMOD |
4.3067693e-05 |
| 9,845 |
Path-centric Cardinality Estimation for Subgraph Matching |
2025 |
VLDB |
4.2680295e-05 |