Balsa: Learning a Query Optimizer Without Expert Demonstrations

Summary: Balsa uses deep RL to learn a query optimizer without expert demonstrations, from a simple simulator to safe real-execution fine-tuning. On Join Order Benchmark, it matches two expert optimizers after ~2 hours and beats them up to 2.8x with training. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6338
Venue: SIGMOD
Year: 2022
Pagerank: 9.5668285e-05
Overall Rank: 2,090 | 85.48%
DOI: 10.1145/3514221.3517885

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 50 of 53 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,345	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1908499e-05
4,464	LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans	2023	VLDB	6.1552798e-05
4,592	Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift	2023	SIGMOD	6.056004e-05
5,339	LEON: A New Framework for ML-Aided Query Optimization	2023	VLDB	5.5596755e-05
5,412	Kepler: Robust Learning for Faster Parametric Query Optimization	2023	SIGMOD	5.5200608e-05
5,654	AutoSteer: Learned Query Optimization for Any SQL Database	2023	VLDB	5.3882121e-05
5,844	Stage: Query Execution Time Prediction in Amazon Redshift	2024	SIGMOD	5.3060581e-05
5,931	FASTgres: Making Learned Query Optimizer Hinting Effective	2023	VLDB	5.2632167e-05
5,941	Eraser: Eliminating Performance Regression on Learned Query Optimizer	2024	VLDB	5.2594013e-05
6,382	Sample-Efficient Cardinality Estimation Using Geometric Deep Learning	2024	VLDB	5.0835686e-05
6,687	How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks	2025	SIGMOD	4.957987e-05
6,862	Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges	2023	VLDB	4.9004921e-05
6,883	PilotScope: Steering Databases with Machine Learning Drivers	2024	VLDB	4.8918682e-05
7,009	Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective	2024	VLDB	4.8597992e-05
7,011	Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis	2023	VLDB	4.8583284e-05
7,220	Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation	2023	SIGMOD	4.7926382e-05
7,326	Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries	2023	SIGMOD	4.7563708e-05
7,676	E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model	2025	VLDB	4.6770108e-05
7,742	Rethinking Learned Cost Models: Why Start from Scratch?	2023	SIGMOD	4.6585812e-05
8,003	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	4.6049527e-05
8,339	SlabCity: Whole-Query Optimization using Program Synthesis	2023	VLDB	4.5383933e-05
8,479	Can Large Language Models Be Query Optimizer for Relational Databases?	2026	SIGMOD	4.4967983e-05
8,660	Learned Offline Query Planning via Bayesian Optimization	2025	SIGMOD	4.4680058e-05
8,961	T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees	2025	SIGMOD	4.4171776e-05
9,012	Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems	2024	VLDB	4.4059413e-05
9,107	BASE: Bridging the Gap between Cost and Latency for Query Optimization	2023	VLDB	4.3907944e-05
9,331	BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach	2023	SIGMOD	4.351469e-05
9,350	LIMAO: A Framework for Lifelong Modular Learned Query Optimization	2025	VLDB	4.3494621e-05
9,581	Low Rank Learning for Offline Query Optimization	2025	SIGMOD	4.3186744e-05
9,628	Approximate Sketches	2024	SIGMOD	4.3102157e-05
9,824	Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement	2025	SIGMOD	4.2710095e-05
9,959	An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL	2025	SIGMOD	4.2254157e-05
10,018	GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints	2026	SIGMOD	4.1905499e-05
10,032	Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads	2026	SIGMOD	4.1905499e-05
10,050	APQO: An Adaptive Framework for Parametric Query Optimization	2026	SIGMOD	4.1905499e-05
10,096	NeuSO: Neural Optimizer for Subgraph Queries	2026	SIGMOD	4.1905499e-05
10,112	SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer	2026	SIGMOD	4.1905499e-05
10,156	Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload	2026	SIGMOD	4.1905499e-05
10,219	Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking	2026	SIGMOD	4.1905499e-05
10,225	LIO: A lightweight and interpretable query optimizer based on an evolutionary forest	2026	VLDB	4.1905499e-05
10,227	Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries	2026	VLDB	4.1905499e-05
10,271	OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning	2026	VLDB	4.1905499e-05
10,282	Toward Drift-Aware Database Benchmarking	2026	VLDB	4.1905499e-05
10,300	TATA: An Efficient Framework for Task Transfer in Query Plan Representation	2026	VLDB	4.1905499e-05
10,635	Robust Plan Evaluation based on Approximate Probabilistic Machine Learning	2025	VLDB	4.1905499e-05
10,638	Conformal Prediction for Verifiable Learned Query Optimization	2025	VLDB	4.1905499e-05
10,733	Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries	2025	VLDB	4.1905499e-05
10,778	veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System	2025	VLDB	4.1905499e-05
10,844	Learned Cost Models for Query Optimization: From Batch to Streaming Systems	2025	VLDB	4.1905499e-05
10,863	Graph Transformers for Query Plan Representation: Potentials and Challenges	2025	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1	Access Path Selection in a Relational Database Management System	1979	SIGMOD	0.0040465394
71	How Good Are Query Optimizers, Really?	2016	VLDB	0.00059446482
203	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00034868567
329	Neo: A Learned Query Optimizer	2019	VLDB	0.00027301488
606	DeepDB: Learn from Data, not from Queries!	2020	VLDB	0.00019251186
634	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018844568
752	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.00017138049
804	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.0001643674
905	NeuroCard: One Cardinality Estimator for All Tables	2021	VLDB	0.00015423174
1,239	Selectivity Estimation for Range Predicates using Lightweight Models	2019	VLDB	0.00013091459
1,427	Towards Scalable Dataframe Systems	2020	VLDB	0.00012033503
1,699	Are We Ready For Learned Cardinality Estimation?	2021	VLDB	0.00010848882
2,080	Towards a Learning Optimizer for Shared Clouds	2019	VLDB	9.5954034e-05
2,222	SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning	2019	SIGMOD	9.2598438e-05
3,066	Learning a Partitioning Advisor for Cloud Databases	2020	SIGMOD	7.6255556e-05
4,352	Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning	2021	VLDB	6.2542257e-05

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7,009	Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective	2024	VLDB	4.8597992e-05
5,994	Steering Query Optimizers: A Practical Take on Big Data Workloads	2021	SIGMOD	5.2367998e-05
5,289	LearnedSQLGen: Constraint-aware SQL Generation using Reinforcement Learning	2022	SIGMOD	5.5790771e-05
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10,638	Conformal Prediction for Verifiable Learned Query Optimization	2025	VLDB	4.1905499e-05
5,654	AutoSteer: Learned Query Optimization for Any SQL Database	2023	VLDB	5.3882121e-05
2,154	SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning	2018	VLDB	9.4176683e-05
9,107	BASE: Bridging the Gap between Cost and Latency for Query Optimization	2023	VLDB	4.3907944e-05
634	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018844568
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