| 320 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021128745 |
| 508 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017108973 |
| 770 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00014086699 |
| 793 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00013903938 |
| 983 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012677179 |
| 1,064 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012181459 |
| 1,065 |
Approximate Query Processing: No Silver Bullet |
2017 |
SIGMOD |
0.00012181098 |
| 1,681 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
9.8821344e-05 |
| 1,740 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7289523e-05 |
| 1,804 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.5971444e-05 |
| 2,635 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
8.1795762e-05 |
| 2,829 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
7.9469964e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 2,987 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.767043e-05 |
| 3,105 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
7.6278115e-05 |
| 3,428 |
Revisiting Reuse for Approximate Query Processing |
2017 |
VLDB |
7.2957009e-05 |
| 3,435 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
7.2845431e-05 |
| 4,011 |
Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins |
2023 |
PODS |
6.842581e-05 |
| 4,315 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
6.6545412e-05 |
| 4,479 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5665703e-05 |
| 4,661 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
6.4656621e-05 |
| 5,271 |
Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach |
2024 |
VLDB |
6.1891764e-05 |
| 5,399 |
At-the-time and Back-in-time Persistent Sketches |
2021 |
SIGMOD |
6.1336701e-05 |
| 5,435 |
Towards Distribution-aware Query Answering in Data Markets |
2022 |
VLDB |
6.1167862e-05 |
| 5,622 |
Responsible Data Integration: Next-generation Challenges |
2022 |
SIGMOD |
6.0460189e-05 |
| 5,671 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
6.026372e-05 |
| 5,717 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
6.0067263e-05 |
| 5,752 |
Tailoring Data Source Distributions for Fairness-aware Data Integration |
2021 |
VLDB |
5.9890389e-05 |
| 5,841 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.9569427e-05 |
| 5,883 |
Leveraging Application Data Constraints to Optimize Database-Backed Web Applications |
2023 |
VLDB |
5.9423067e-05 |
| 5,885 |
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees |
2019 |
SIGMOD |
5.9421702e-05 |
| 6,014 |
Approximate Query Engines: Commercial Challenges and Research Opportunities |
2017 |
SIGMOD |
5.8956963e-05 |
| 6,061 |
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration |
2021 |
SIGMOD |
5.8831543e-05 |
| 6,485 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
5.7525455e-05 |
| 6,812 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6597129e-05 |
| 6,840 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.6513231e-05 |
| 7,175 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
5.5779755e-05 |
| 7,387 |
Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries |
2021 |
SIGMOD |
5.5212177e-05 |
| 7,624 |
Scalable Approximate Butterfly and Bi-triangle Counting for Large Bipartite Networks |
2023 |
SIGMOD |
5.4661079e-05 |
| 7,626 |
Privacy Amplification by Sampling under User-level Differential Privacy |
2024 |
SIGMOD |
5.4657865e-05 |
| 7,675 |
Continuous Prefetch for Interactive Data Applications |
2020 |
VLDB |
5.4565877e-05 |
| 7,720 |
Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams |
2022 |
VLDB |
5.4542911e-05 |
| 7,902 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
5.4135994e-05 |
| 7,950 |
Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines |
2024 |
VLDB |
5.402957e-05 |
| 8,300 |
Subset Sampling over Joins |
2026 |
PODS |
5.3434957e-05 |
| 8,305 |
Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters |
2019 |
VLDB |
5.3427507e-05 |
| 8,685 |
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation |
2023 |
VLDB |
5.2730954e-05 |
| 8,769 |
ProgressiveDB – Progressive Data Analytics as a Middleware |
2019 |
VLDB |
5.2691244e-05 |
| 8,872 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
5.2459616e-05 |
| 8,915 |
FastPDB: Towards Bag-Probabilistic Queries at Interactive Speeds |
2025 |
SIGMOD |
5.2361195e-05 |