Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift

Summary: Auto-WLM is ML-driven WLM for Redshift that auto-tunes concurrency and memory to maximize throughput under workloads. Locally trained query performance models predict runtime and memory to guide millions of scheduling decisions in real time. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6501
Venue: SIGMOD
Year: 2023
Pagerank: 6.0606891e-05
Overall Rank: 4,593 | 68.05%
DOI: 10.1145/3555041.3589677

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 23 of 23 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,178	Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet	2024	VLDB	7.4325992e-05
5,634	Intelligent Scaling in Amazon Redshift	2024	SIGMOD	5.4000904e-05
5,832	Stage: Query Execution Time Prediction in Amazon Redshift	2024	SIGMOD	5.3111109e-05
7,828	Modeling Shifting Workloads for Learned Database Systems	2024	SIGMOD	4.6407986e-05
7,990	Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD	2024	VLDB	4.6117441e-05
8,225	Automated Multidimensional Data Layouts in Amazon Redshift	2024	SIGMOD	4.555289e-05
8,834	ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation	2024	SIGMOD	4.4394021e-05
8,956	T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees	2025	SIGMOD	4.4214154e-05
9,213	PACE: Poisoning Attacks on Learned Cardinality Estimation	2024	SIGMOD	4.3721075e-05
9,230	LeaFi: Data Series Indexes on Steroids with Learned Filters	2025	SIGMOD	4.3690661e-05
10,216	The Case For Language Model Approximated LIKE Predicate	2026	SIGMOD	4.1945683e-05
10,265	AQD: Online Adaptive Query Dispatcher for HTAP Databases	2026	VLDB	4.1945683e-05
10,310	SafeLoad: Efficient Admission Control Framework for Identifying Memory-Overloading Queries in Cloud Data Warehouses	2026	VLDB	4.1945683e-05
10,405	Flux: Unifying Heterogeneous Infrastructure for Alibaba AnalyticDB	2025	SIGMOD	4.1945683e-05
10,491	Intra-Query Runtime Elasticity for Cloud-Native Data Analysis	2025	SIGMOD	4.1945683e-05
10,564	PlanRGCN: Predicting SPARQL Query Performance	2025	VLDB	4.1945683e-05
10,707	PBench: Workload Synthesizer with Real Statistics for Cloud Analytics Benchmarking	2025	VLDB	4.1945683e-05
10,726	Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries	2025	VLDB	4.1945683e-05
10,840	Learned Cost Models for Query Optimization: From Batch to Streaming Systems	2025	VLDB	4.1945683e-05
10,852	CloudGlide: Deconstructing the Landscape of Cloud-Based Analytics	2025	VLDB	4.1945683e-05
10,872	LASER: Buffer-Aware Learned Query Scheduling in Master-Standby Databases	2025	VLDB	4.1945683e-05
10,932	Flux: Decoupled Auto-Scaling for Heterogeneous Query Workload in Alibaba AnalyticDB	2024	SIGMOD	4.1945683e-05
10,987	DPconv: Super-Polynomially Faster Join Ordering	2024	SIGMOD	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 33 of 33 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
71	How Good Are Query Optimizers, Really?	2016	VLDB	0.00059038975
102	The Case for Learned Index Structures	2018	SIGMOD	0.00049545203
183	Automatic Database Management System Tuning Through Large-scale Machine Learning	2017	SIGMOD	0.00036721403
204	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00034784455
209	Schism: a Workload-Driven Approach to Database Replication and Partitioning	2010	VLDB	0.00034468292
300	Deep Learning for Entity Matching: A Design Space Exploration	2018	SIGMOD	0.00028441466
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
359	Self-Driving Database Management Systems	2017	CIDR	0.0002592783
424	Tuning Database Configuration Parameters with iTuned	2009	VLDB	0.00023616398
640	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018759152
758	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.0001706608
801	SageDB: A Learned Database System	2019	CIDR	0.00016505496
857	The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds	2020	VLDB	0.00015882892
884	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.00015654004
1,284	Amazon Redshift Re-invented	2022	SIGMOD	0.00012837822
1,478	Learning Multi-dimensional Indexes	2020	SIGMOD	0.00011762542
1,855	AI Meets AI: Leveraging Query Executions to Improve Index Recommendations	2019	SIGMOD	0.00010315245
1,889	Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads	2021	VLDB	0.00010200865
2,047	Automatically Indexing Millions of Databases in Microsoft Azure SQL Database	2019	SIGMOD	9.6920209e-05
2,121	Balsa: Learning a Query Optimizer Without Expert Demonstrations	2022	SIGMOD	9.5017232e-05
2,156	SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning	2018	VLDB	9.4170209e-05
2,307	On Predictive Modeling for Optimizing Transaction Execution in Parallel OLTP Systems	2012	VLDB	9.0599752e-05
2,772	Quickstep: A Data Platform Based on the Scaling-Up Approach	2018	VLDB	8.1401661e-05
3,216	WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases	2016	VLDB	7.3601267e-05
3,828	Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction	2022	VLDB	6.7208524e-05
4,417	Robust Query Driven Cardinality Estimation under Changing Workloads	2023	VLDB	6.2037371e-05
4,549	Database-Agnostic Workload Management	2019	CIDR	6.0926728e-05
4,690	Deploying a Steered Query Optimizer in Production at Microsoft	2022	SIGMOD	5.997226e-05
4,961	Releasing Cloud Databases from the Chains of Performance Prediction Models	2017	CIDR	5.7984657e-05
5,212	Self-Tuning Query Scheduling for Analytical Workloads	2021	SIGMOD	5.6262923e-05
5,451	NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning	2018	SIGMOD	5.5002949e-05
5,671	LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems	2022	SIGMOD	5.3803919e-05
6,040	Steering Query Optimizers: A Practical Take on Big Data Workloads	2021	SIGMOD	5.2412035e-05

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6,456	From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems	2019	SIGMOD	5.0564619e-05
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1,827	An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems	2021	VLDB	0.00010390548
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3,844	The evolution of Amazon Redshift (extended abstract)	2021	VLDB	6.7076451e-05
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