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The Relational Data Borg is Learning
Summary: Recasts machine learning on relational data as query processing: feature extraction plus group-by aggregates. An algebraic, statistical, and systems toolbox exploits data structure, specialization, sharing, and parallelism to reduce learning complexity and constants.
(summarized by gpt-5.6-luna on Jul 24 2026)
Paper ID
ha397f72c41e48f25
Venue
VLDB
Year
2020
Pagerank
6.7669004e-05
Overall Rank
4,161 | 72.04%
DOI
10.14778/3415478.3415572
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(CC BY-NC-ND 4.0)
Incoming Non-self Citations Over Time
BibTeX Citation
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@article{olteanu_vldb20,
title = {{The Relational Data Borg is Learning}},
author = {Olteanu, Dan},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {12},
pages = {3502--3515},
doi = {10.14778/3415478.3415572},
url = {https://doi.org/10.14778/3415478.3415572},
year = {2020}
}
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2,189
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2021
SIGMOD
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2022
SIGMOD
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2023
VLDB
6.082972e-05
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2022
VLDB
5.6647722e-05
8,080
Tight Bounds of Circuits for Sum-Product Queries
2024
PODS
5.3917406e-05
8,389
AWARE: Workload-aware, Redundancy-exploiting Linear Algebra
2023
SIGMOD
5.3396465e-05
10,515
SPALM: A Sparsity-Pattern-Adaptive Library for Matrices
2026
SIGMOD
4.9769913e-05
10,749
Database Views as Explanations for Relational Deep Learning
2026
VLDB
4.9769913e-05
10,954
Morphing-based Compression for Data-centric ML Pipelines
2026
VLDB
4.9769913e-05
11,797
Demonstration of OpenDBML, a Framework for Democratizing In-Database Machine Learning
2023
VLDB
4.9769913e-05
11,876
Givens QR Decomposition over Relational Databases
2022
SIGMOD
4.9769913e-05
Outgoing Citations (Sorted by Pagerank)
Showing 30 of 30 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Rank
Cited Paper
Year
Venue
Pagerank
21
Efficiently Compiling Efficient Query Plans for Modern Hardware
2011
VLDB
0.00056835296
105
The MADlib Analytics Library or MAD Skills, the SQL
2012
VLDB
0.00033633007
135
Ripple Joins for Online Aggregation
1999
SIGMOD
0.00029858107
208
EmptyHeaded: A Relational Engine for Graph Processing
2016
SIGMOD
0.00024899872
357
FAQ: Questions Asked Frequently
2016
PODS
0.00020013731
402
Worst-case Optimal Join Algorithms
2012
PODS
0.00019095982
408
DBToaster: Higher-order Delta Processing for Dynamic, Frequently Fresh Views
2012
VLDB
0.00018894165
466
Design and Implementation of the LogicBlox System
2015
SIGMOD
0.00017765702
503
Towards a Unified Architecture for in-RDBMS Analytics
2012
SIGMOD
0.00017195428
521
Learning Linear Regression Models over Factorized Joins
2016
SIGMOD
0.00016923519
731
Learning Generalized Linear Models Over Normalized Data
2015
SIGMOD
0.00014400356
849
Aggregation and Ordering in Factorised Databases
2013
VLDB
0.00013498306
918
Accelerating XPath Location Steps
2002
SIGMOD
0.00013078274
977
Incremental Query Evaluation in a Ring of Databases
2010
PODS
0.00012730241
1,091
What do Shannon-type Inequalities, Submodular Width, and Disjunctive Datalog have to do with one another?
2017
PODS
0.00012068611
1,153
Data Management Challenges in Production Machine Learning
2017
SIGMOD
0.00011793347
1,223
Data Management in Machine Learning: Challenges, Techniques, and Systems
2017
SIGMOD
0.00011468426
1,744
How to Architect a Query Compiler
2016
SIGMOD
9.7332903e-05
2,293
FDB: A Query Engine for Factorised Relational Databases
2012
VLDB
8.685044e-05
2,302
On Functional Aggregate Queries with Additive Inequalities
2019
PODS
8.6687541e-05
2,418
The Semiring Framework for Database Provenance
2017
PODS
8.4904382e-05
2,663
A Layered Aggregate Engine for Analytics Workloads
2019
SIGMOD
8.1542952e-05
2,978
In-Database Learning with Sparse Tensors
2018
PODS
7.7872011e-05
3,114
Incremental View Maintenance with Triple Lock Factorization Benefits
2018
SIGMOD
7.6321464e-05
3,188
Trade-offs in Static and Dynamic Evaluation of Hierarchical Queries
2020
PODS
7.5510881e-05
3,373
F: Regression Models over Factorized Views
2016
VLDB
7.3627128e-05
4,702
F-IVM: Learning over Fast-Evolving Relational Data
2020
SIGMOD
6.46033e-05
5,636
LMFAO: An Engine for Batches of Group-By Aggregates
2020
VLDB
6.0549222e-05
5,877
BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees
2019
SIGMOD
5.9599042e-05
8,843
Three Modern Roles for Logic in AI
2020
PODS
5.265121e-05
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