Back to papers
SafeBound: A Practical System for Generating Cardinality Bounds
Summary: SafeBound is the first practical system for guaranteed upper bounds on cardinalities with predicate support. Extends degree-sequence bounds via compression and inference, delivering up to 80% gains vs PostgreSQL and 500x faster planning, with less space.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6556
- Venue
- SIGMOD
- Year
- 2023
- Pagerank
- 5.2474768e-05
- Overall Rank
- 5,972 | 58.46%
- DOI
-
10.1145/3588907
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 15 of 15 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 6,969 |
LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences |
2025 |
SIGMOD |
4.8799937e-05 |
| 7,123 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
4.8251036e-05 |
| 7,344 |
Join Size Bounds using l_p-Norms on Degree Sequences |
2024 |
PODS |
4.7565607e-05 |
| 8,279 |
Galley: Modern Query Optimization for Sparse Tensor Programs |
2025 |
SIGMOD |
4.5435639e-05 |
| 9,747 |
Still Asking: How Good Are Query Optimizers, Really? |
2025 |
VLDB |
4.2897489e-05 |
| 9,812 |
A Practical Theory of Generalization in Selectivity Learning |
2025 |
VLDB |
4.2783272e-05 |
| 9,825 |
Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement |
2025 |
SIGMOD |
4.2751057e-05 |
| 9,843 |
Efficient Algorithms for Cardinality Estimation and Conjunctive Query Evaluation With Simple Degree Constraints |
2025 |
PODS |
4.2721228e-05 |
| 9,845 |
Path-centric Cardinality Estimation for Subgraph Matching |
2025 |
VLDB |
4.2721228e-05 |
| 9,877 |
Color: A Framework for Applying Graph Coloring to Subgraph Cardinality Estimation |
2025 |
VLDB |
4.2656547e-05 |
| 9,960 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
4.2294678e-05 |
| 9,988 |
I Can't Believe It's Not Yannakakis: Pragmatic Bitmap Filters in Microsoft SQL Server |
2026 |
CIDR |
4.1945683e-05 |
| 10,149 |
CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,619 |
Data-Agnostic Cardinality Learning from Imperfect Workloads |
2025 |
VLDB |
4.1945683e-05 |
| 10,983 |
A Universal Sketch for Estimating Heavy Hitters and Per-Element Frequency Moments in Data Streams with Bounded Deletions |
2024 |
SIGMOD |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 586 |
DBToaster: Higher-order Delta Processing for Dynamic, Frequently Fresh Views |
2012 |
VLDB |
0.00019685374 |
| 608 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019235898 |
| 857 |
The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds |
2020 |
VLDB |
0.00015882892 |
| 910 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423056 |
| 1,442 |
What do Shannon-type Inequalities, Submodular Width, and Disjunctive Datalog have to do with one another? |
2017 |
PODS |
0.00011956109 |
| 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 |
| 2,142 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4507296e-05 |
| 2,762 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1585394e-05 |
| 2,783 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1293383e-05 |
| 3,266 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
7.3074684e-05 |
| 3,499 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
7.0376445e-05 |
| 3,511 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.0254052e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6271553e-05 |
| 4,523 |
Simplicity Done Right for Join Ordering |
2021 |
CIDR |
6.1135504e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
6.1011198e-05 |
| 6,824 |
Computing Join Queries with Functional Dependencies |
2016 |
PODS |
4.9144789e-05 |
Semantically Similar Papers