| 40 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
220 |
0.00046363107 |
| 92 |
CrowdDB: Answering Queries with Crowdsourcing |
2011 |
SIGMOD |
77 |
0.00034670735 |
| 144 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
179 |
0.00029090793 |
| 198 |
CrowdER: Crowdsourcing Entity Resolution |
2012 |
VLDB |
71 |
0.00025546182 |
| 361 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
130 |
0.00020000855 |
| 422 |
ALEX: An Updatable Adaptive Learned Index |
2020 |
SIGMOD |
105 |
0.00018488849 |
| 537 |
MLbase: A Distributed Machine-learning System |
2013 |
CIDR |
34 |
0.00016762761 |
| 555 |
SageDB: A Learned Database System |
2019 |
CIDR |
63 |
0.0001650754 |
| 647 |
Building a Database on S3 |
2008 |
SIGMOD |
34 |
0.00015201469 |
| 717 |
Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing |
2025 |
CIDR |
46 |
0.00014528323 |
| 768 |
FITing-Tree: A Data-aware Index Structure |
2019 |
SIGMOD |
70 |
0.00014107655 |
| 835 |
Benchmarking Learned Indexes |
2021 |
VLDB |
61 |
0.00013575971 |
| 869 |
Learning Multi-dimensional Indexes |
2020 |
SIGMOD |
74 |
0.00013363241 |
| 871 |
Leveraging Transitive Relations for Crowdsourced Joins |
2013 |
SIGMOD |
35 |
0.00013338722 |
| 945 |
The End of Slow Networks: It's Time for a Redesign |
2016 |
VLDB |
48 |
0.00012933247 |
| 976 |
Democratizing Data Science through Interactive Curation of ML Pipelines |
2019 |
SIGMOD |
28 |
0.0001274453 |
| 1,023 |
MIRIS: Fast Object Track Queries in Video |
2020 |
SIGMOD |
37 |
0.00012430702 |
| 1,038 |
ARDA: Automatic Relational Data Augmentation for Machine Learning |
2020 |
VLDB |
35 |
0.000123653 |
| 1,188 |
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads |
2021 |
VLDB |
61 |
0.00011598149 |
| 1,322 |
An Evaluation of Alternative Architectures for Transaction Processing in the Cloud |
2010 |
SIGMOD |
13 |
0.00011029244 |
| 1,339 |
The End of a Myth: Distributed Transactions Can Scale |
2017 |
VLDB |
46 |
0.0001097043 |
| 1,366 |
Designing Distributed Tree-based Index Structures for Fast RDMA-capable Networks |
2019 |
SIGMOD |
35 |
0.00010908555 |
| 1,408 |
Northstar: An Interactive Data Science System |
2018 |
VLDB |
21 |
0.00010738859 |
| 1,445 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
33 |
0.00010628379 |
| 1,447 |
Consistency Rationing in the Cloud: Pay only when it matters |
2009 |
VLDB |
20 |
0.00010622872 |
| 1,722 |
A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data |
2014 |
SIGMOD |
38 |
9.7921604e-05 |
| 1,735 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
60 |
9.7566604e-05 |
| 1,797 |
IDEBench: A Benchmark for Interactive Data Exploration |
2020 |
SIGMOD |
26 |
9.6143465e-05 |
| 1,803 |
Tuplex: Data Science in Python at Native Code Speed |
2021 |
SIGMOD |
20 |
9.602292e-05 |
| 1,834 |
Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet |
2024 |
VLDB |
37 |
9.5349903e-05 |
| 1,852 |
CrowdDB: Query Processing with the VLDB Crowd |
2011 |
VLDB |
14 |
9.4992704e-05 |
| 1,879 |
Making the Case for Query-by-Voice with EchoQuery |
2016 |
SIGMOD |
13 |
9.4489661e-05 |
| 1,939 |
S-Store: Streaming Meets Transaction Processing |
2015 |
VLDB |
22 |
9.3299482e-05 |
| 2,009 |
PIQL: Success-Tolerant Query Processing in the Cloud |
2012 |
VLDB |
19 |
9.1949132e-05 |
| 2,097 |
Vizdom: Interactive Analytics through Pen and Touch |
2015 |
VLDB |
29 |
9.0525341e-05 |
| 2,125 |
Tupleware: "Big" Data, Big Analytics, Small Clusters |
2015 |
CIDR |
20 |
9.0017828e-05 |
| 2,492 |
A Demonstration of the BigDAWG Polystore System |
2015 |
VLDB |
13 |
8.3861255e-05 |
| 2,765 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
28 |
8.0401855e-05 |
| 2,829 |
DB4ML – An In-Memory Database Kernel with Machine Learning Support |
2020 |
SIGMOD |
13 |
7.9592539e-05 |
| 2,839 |
SNARF: A Learning-Enhanced Range Filter |
2022 |
VLDB |
20 |
7.9490277e-05 |
| 2,840 |
Towards Sustainable Insights or why polygamy is bad for you |
2017 |
CIDR |
6 |
7.948968e-05 |
| 2,844 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
35 |
7.9446987e-05 |
| 2,968 |
Choosing A Cloud DBMS: Architectures and Tradeoffs |
2019 |
VLDB |
20 |
7.8004755e-05 |
| 3,049 |
Abacus: A Cost-Based Optimizer for Semantic Operator Systems |
2026 |
VLDB |
18 |
7.7087759e-05 |
| 3,160 |
S-Store: A Streaming NewSQL System for Big Velocity Applications |
2014 |
VLDB |
14 |
7.5773134e-05 |
| 3,171 |
Panda: Performance Debugging for Databases using LLM Agents |
2024 |
CIDR |
12 |
7.5661555e-05 |
| 3,198 |
CDFShop: Exploring and Optimizing Learned Index Structures |
2020 |
SIGMOD |
21 |
7.5422544e-05 |
| 3,233 |
TreeLine: An Update-In-Place Key-Value Store for Modern Storage |
2023 |
VLDB |
26 |
7.5008192e-05 |
| 3,271 |
Rethinking Database High Availability with RDMA Networks |
2019 |
VLDB |
17 |
7.4716945e-05 |
| 3,281 |
Controlling False Discoveries During Interactive Data Exploration |
2017 |
SIGMOD |
9 |
7.4574856e-05 |
| 3,327 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
37 |
7.4233639e-05 |
| 3,391 |
RTP: Robust Tenant Placement for Elastic In-Memory Database Clusters |
2013 |
SIGMOD |
8 |
7.3462108e-05 |
| 3,417 |
Revisiting Reuse for Approximate Query Processing |
2017 |
VLDB |
22 |
7.3184905e-05 |
| 3,464 |
DBOS: A DBMS-oriented Operating System |
2022 |
VLDB |
16 |
7.2788609e-05 |
| 3,565 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
25 |
7.200937e-05 |
| 3,651 |
Davos: A System for Interactive Data-Driven Decision Making |
2021 |
VLDB |
4 |
7.1336875e-05 |
| 3,708 |
The Case for a Learned Sorting Algorithm |
2020 |
SIGMOD |
17 |
7.0781032e-05 |
| 3,718 |
Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype? |
2015 |
SIGMOD |
7 |
7.0703796e-05 |
| 4,174 |
Resource Management in Aurora Serverless |
2024 |
VLDB |
10 |
6.7552862e-05 |
| 4,322 |
Generalized Scale Independence Through Incremental Precomputation |
2013 |
SIGMOD |
7 |
6.6629734e-05 |
| 4,558 |
Databases Unbound: Querying All of the World’s Bytes with AI |
2024 |
VLDB |
7 |
6.5333125e-05 |
| 4,668 |
Intelligent Scaling in Amazon Redshift |
2024 |
SIGMOD |
13 |
6.4768105e-05 |
| 4,890 |
Can Learned Models Replace Hash Functions? |
2023 |
VLDB |
8 |
6.3663299e-05 |
| 4,962 |
PrivateClean: Data Cleaning and Differential Privacy |
2016 |
SIGMOD |
4 |
6.3360478e-05 |
| 5,043 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
16 |
6.2979214e-05 |
| 5,110 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
22 |
6.2678118e-05 |
| 5,216 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
21 |
6.2218868e-05 |
| 5,320 |
Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks |
2020 |
SIGMOD |
16 |
6.1813707e-05 |
| 5,470 |
Crowdsourcing Applications and Platforms: A Data Management Perspective |
2011 |
VLDB |
4 |
6.1173893e-05 |
| 5,615 |
CrowdQ: Crowdsourced Query Understanding |
2013 |
CIDR |
2 |
6.0640551e-05 |
| 5,638 |
Revisiting Reuse in Main Memory Database Systems |
2017 |
SIGMOD |
11 |
6.0546358e-05 |
| 5,929 |
Self-Organizing Data Containers |
2022 |
CIDR |
7 |
5.9411211e-05 |
| 5,973 |
Towards instance-optimized data systems |
2021 |
VLDB |
7 |
5.9281867e-05 |
| 6,027 |
Automated Multidimensional Data Layouts in Amazon Redshift |
2024 |
SIGMOD |
9 |
5.9089922e-05 |
| 6,081 |
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems |
2019 |
SIGMOD |
11 |
5.8897947e-05 |
| 6,240 |
Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses |
2024 |
SIGMOD |
13 |
5.8373399e-05 |
| 6,455 |
XQuery in the Browser |
2008 |
SIGMOD |
3 |
5.7770889e-05 |
| 6,514 |
PLANET: Making Progress with Commit Processing in Unpredictable Environments |
2014 |
SIGMOD |
3 |
5.7570121e-05 |
| 6,586 |
Extract-Transform-Load for Video Streams |
2023 |
VLDB |
9 |
5.741099e-05 |
| 6,885 |
Estimating the Impact of Unknown Unknowns on Aggregate Query Results |
2016 |
SIGMOD |
8 |
5.6546466e-05 |
| 7,604 |
SageDB: An Instance-Optimized Data Analytics System |
2022 |
VLDB |
8 |
5.4846038e-05 |
| 7,727 |
Extending XQuery with Window Functions |
2007 |
VLDB |
5 |
5.4652337e-05 |
| 7,759 |
XQuery Reloaded |
2009 |
VLDB |
2 |
5.4567128e-05 |
| 7,810 |
Parachute: Single-Pass Bi-Directional Information Passing |
2025 |
VLDB |
5 |
5.4477354e-05 |
| 7,869 |
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD |
2024 |
VLDB |
6 |
5.4342182e-05 |
| 8,402 |
The Case for Learned In-Memory Joins |
2023 |
VLDB |
5 |
5.3375308e-05 |
| 8,643 |
PBench: Workload Synthesizer with Real Statistics for Cloud Analytics Benchmarking |
2025 |
VLDB |
2 |
5.2956539e-05 |
| 8,876 |
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views |
2015 |
VLDB |
10 |
5.2587627e-05 |
| 9,124 |
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes |
2023 |
VLDB |
6 |
5.2247088e-05 |
| 9,394 |
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets |
2017 |
VLDB |
2 |
5.1843659e-05 |
| 9,778 |
Cost-based Fault-tolerance for Parallel Data Processing |
2015 |
SIGMOD |
1 |
5.1294772e-05 |
| 9,944 |
Approximate Query Processing for Interactive Data Science |
2017 |
SIGMOD |
1 |
5.1043915e-05 |
| 10,052 |
Tuplex: Robust, Efficient Analytics When Python Rules |
2019 |
VLDB |
1 |
5.0890428e-05 |
| 10,148 |
Deep Research is the New Analytics System: Towards Building the Runtime for AI-Driven Analytics |
2026 |
CIDR |
1 |
5.0691578e-05 |
| 10,152 |
Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries |
2025 |
VLDB |
1 |
5.0691578e-05 |
| 10,918 |
Incremental Query Optimizer Statistics in Amazon Redshift |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 10,989 |
Carnot: Interpretable, Interactive, and Optimized Execution of Deep Research Queries |
2026 |
VLDB |
0 |
4.9769913e-05 |
| 11,179 |
Virtualizing Cloud Data Infrastructures with BRAD |
2025 |
SIGMOD |
0 |
4.9769913e-05 |
| 12,295 |
Safe Visual Data Exploration |
2017 |
SIGMOD |
1 |
4.9769913e-05 |
| 12,744 |
Cloudy: A Modular Cloud Storage System |
2010 |
VLDB |
0 |
4.9769913e-05 |
| 13,921 |
Should we all be teaching “Intro to Data Science” instead of “Intro to Databases”? |
2014 |
SIGMOD |
0 |
- |