| 608 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019235898 |
| 910 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423056 |
| 1,204 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013319541 |
| 1,369 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00012339777 |
| 1,574 |
Approximate Query Processing: No Silver Bullet |
2017 |
SIGMOD |
0.00011287495 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011049779 |
| 1,703 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010836769 |
| 2,129 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
9.480002e-05 |
| 2,254 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
9.1897043e-05 |
| 2,783 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1293383e-05 |
| 3,001 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
7.7404487e-05 |
| 3,511 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.0254052e-05 |
| 3,646 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8853079e-05 |
| 3,778 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
6.7747398e-05 |
| 3,944 |
AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics |
2018 |
SIGMOD |
6.6078243e-05 |
| 3,990 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5581983e-05 |
| 4,030 |
Revisiting Reuse for Approximate Query Processing |
2017 |
VLDB |
6.5129665e-05 |
| 4,434 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.1929999e-05 |
| 5,024 |
Towards Distribution-aware Query Answering in Data Markets |
2022 |
VLDB |
5.7535043e-05 |
| 5,104 |
Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins |
2023 |
PODS |
5.6946113e-05 |
| 5,150 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
5.6626586e-05 |
| 5,401 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
5.5285035e-05 |
| 5,806 |
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees |
2019 |
SIGMOD |
5.3200643e-05 |
| 5,909 |
At-the-time and Back-in-time Persistent Sketches |
2021 |
SIGMOD |
5.2769377e-05 |
| 5,951 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
5.2592385e-05 |
| 5,976 |
Responsible Data Integration: Next-generation Challenges |
2022 |
SIGMOD |
5.245976e-05 |
| 6,208 |
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration |
2021 |
SIGMOD |
5.1568586e-05 |
| 6,289 |
Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach |
2024 |
VLDB |
5.1275309e-05 |
| 6,411 |
Approximate Query Engines: Commercial Challenges and Research Opportunities |
2017 |
SIGMOD |
5.0752468e-05 |
| 6,467 |
Tailoring Data Source Distributions for Fairness-aware Data Integration |
2021 |
VLDB |
5.0528156e-05 |
| 6,493 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.0424713e-05 |
| 6,704 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
4.9554912e-05 |
| 6,714 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
4.9512171e-05 |
| 6,907 |
Continuous Prefetch for Interactive Data Applications |
2020 |
VLDB |
4.8925595e-05 |
| 7,123 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
4.8251036e-05 |
| 7,251 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
4.7890519e-05 |
| 7,358 |
Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries |
2021 |
SIGMOD |
4.7529363e-05 |
| 7,451 |
Scalable Approximate Butterfly and Bi-triangle Counting for Large Bipartite Networks |
2023 |
SIGMOD |
4.7263711e-05 |
| 7,534 |
Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams |
2022 |
VLDB |
4.7180004e-05 |
| 7,714 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
4.6700455e-05 |
| 7,854 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
4.6350172e-05 |
| 8,080 |
Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines |
2024 |
VLDB |
4.5911668e-05 |
| 8,240 |
Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters |
2019 |
VLDB |
4.5522563e-05 |
| 8,622 |
ProgressiveDB – Progressive Data Analytics as a Middleware |
2019 |
VLDB |
4.4834877e-05 |
| 8,775 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
4.4553047e-05 |
| 8,873 |
Privacy Amplification by Sampling under User-level Differential Privacy |
2024 |
SIGMOD |
4.4313867e-05 |
| 9,410 |
Leveraging Application Data Constraints to Optimize Database-Backed Web Applications |
2023 |
VLDB |
4.3441378e-05 |
| 9,621 |
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation |
2023 |
VLDB |
4.3167167e-05 |
| 9,652 |
Secure Sampling for Approximate Multi-party Query Processing |
2023 |
SIGMOD |
4.3109001e-05 |
| 9,845 |
Path-centric Cardinality Estimation for Subgraph Matching |
2025 |
VLDB |
4.2721228e-05 |