| 323 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021264788 |
| 513 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017190574 |
| 772 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00014147905 |
| 802 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00013907725 |
| 1,061 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012369764 |
| 1,108 |
Approximate Query Processing: No Silver Bullet |
2017 |
SIGMOD |
0.00012145154 |
| 1,122 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.0001209124 |
| 1,664 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
0.00010070362 |
| 1,767 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.805856e-05 |
| 1,876 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.5717543e-05 |
| 2,731 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
8.1959181e-05 |
| 2,940 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
7.9381573e-05 |
| 2,991 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.8880723e-05 |
| 3,070 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.7900444e-05 |
| 3,283 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
7.56675e-05 |
| 3,366 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
7.4748604e-05 |
| 3,370 |
Revisiting Reuse for Approximate Query Processing |
2017 |
VLDB |
7.4700891e-05 |
| 3,941 |
Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins |
2023 |
PODS |
7.0074268e-05 |
| 4,349 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
6.7504619e-05 |
| 4,368 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.7393882e-05 |
| 4,630 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
6.5955933e-05 |
| 5,255 |
At-the-time and Back-in-time Persistent Sketches |
2021 |
SIGMOD |
6.2982495e-05 |
| 5,300 |
Towards Distribution-aware Query Answering in Data Markets |
2022 |
VLDB |
6.2751506e-05 |
| 5,510 |
Responsible Data Integration: Next-generation Challenges |
2022 |
SIGMOD |
6.1919207e-05 |
| 5,551 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
6.1782856e-05 |
| 5,631 |
Tailoring Data Source Distributions for Fairness-aware Data Integration |
2021 |
VLDB |
6.1427477e-05 |
| 5,743 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
6.1025457e-05 |
| 5,785 |
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees |
2019 |
SIGMOD |
6.0892672e-05 |
| 5,906 |
Approximate Query Engines: Commercial Challenges and Research Opportunities |
2017 |
SIGMOD |
6.0457047e-05 |
| 5,938 |
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration |
2021 |
SIGMOD |
6.0343238e-05 |
| 5,942 |
Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach |
2024 |
VLDB |
6.0334209e-05 |
| 6,325 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
5.9125893e-05 |
| 6,341 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
5.9068986e-05 |
| 6,704 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.797374e-05 |
| 7,048 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
5.7178054e-05 |
| 7,193 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6770249e-05 |
| 7,256 |
Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries |
2021 |
SIGMOD |
5.6625146e-05 |
| 7,455 |
Scalable Approximate Butterfly and Bi-triangle Counting for Large Bipartite Networks |
2023 |
SIGMOD |
5.6127752e-05 |
| 7,456 |
Privacy Amplification by Sampling under User-level Differential Privacy |
2024 |
SIGMOD |
5.6124452e-05 |
| 7,510 |
Continuous Prefetch for Interactive Data Applications |
2020 |
VLDB |
5.6029996e-05 |
| 7,551 |
Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams |
2022 |
VLDB |
5.6006414e-05 |
| 7,721 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
5.5587371e-05 |
| 7,847 |
Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines |
2024 |
VLDB |
5.5330423e-05 |
| 8,108 |
Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters |
2019 |
VLDB |
5.4850569e-05 |
| 8,492 |
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation |
2023 |
VLDB |
5.4145838e-05 |
| 8,578 |
ProgressiveDB – Progressive Data Analytics as a Middleware |
2019 |
VLDB |
5.4091471e-05 |
| 8,698 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
5.3830073e-05 |
| 8,724 |
FastPDB: Towards Bag-Probabilistic Queries at Interactive Speeds |
2025 |
SIGMOD |
5.3766157e-05 |
| 9,392 |
A Step Toward Deep Online Aggregation |
2023 |
SIGMOD |
5.2755515e-05 |
| 9,561 |
Leveraging Application Data Constraints to Optimize Database-Backed Web Applications |
2023 |
VLDB |
5.2528121e-05 |