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Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All?
Summary: Advocates Query Optimizer as a Service (QOaaS) in unified LakeHouse stacks to centralize workload-level optimization and enable multi-engine federation instead of per-engine or library-shared QOs. Shares experience extending Calcite/Cascades across SQL Server, Fabric DW, SCOPE and Spark prototypes, reporting early wins and substantial engineering and semantic challenges.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 564
- Venue
- CIDR
- Year
- 2025
- Pagerank
- 4.4877266e-05
- Overall Rank
- 8,579 | 40.38%
- DOI
-
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Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 21 of 21 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 22 |
SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets |
2008 |
VLDB |
0.00084679526 |
| 329 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027301488 |
| 542 |
Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources |
2018 |
SIGMOD |
0.00020522627 |
| 1,008 |
Spanner: Becoming a SQL System |
2017 |
SIGMOD |
0.00014663067 |
| 1,632 |
Garlic: A New Flavor of Federated Query Processing for DB2 |
2002 |
SIGMOD |
0.00011070537 |
| 1,818 |
A Demonstration of the BigDAWG Polystore System |
2015 |
VLDB |
0.00010418381 |
| 2,080 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
9.5954034e-05 |
| 2,247 |
Orca: A Modular Query Optimizer Architecture for Big Data |
2014 |
SIGMOD |
9.201975e-05 |
| 2,533 |
Velox: Meta’s Unified Execution Engine |
2022 |
VLDB |
8.5870599e-05 |
| 2,693 |
Greenplum: A Hybrid Database for Transactional and Analytical Workloads |
2021 |
SIGMOD |
8.2845883e-05 |
| 3,269 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
7.3026051e-05 |
| 3,623 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9017341e-05 |
| 4,171 |
Computation Reuse in Analytics Job Service at Microsoft |
2018 |
SIGMOD |
6.3800823e-05 |
| 4,180 |
LlamaTune: Sample-Efficient DBMS Configuration Tuning |
2022 |
VLDB |
6.3725334e-05 |
| 4,241 |
The Composable Data Management System Manifesto |
2023 |
VLDB |
6.3258298e-05 |
| 4,687 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
5.9915268e-05 |
| 5,639 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
5.3972261e-05 |
| 5,994 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
5.2367998e-05 |
| 7,203 |
Unified Query Optimization in the Fabric Data Warehouse |
2024 |
SIGMOD |
4.7968914e-05 |
| 8,859 |
Pipemizer: An Optimizer for Analytics Data Pipelines |
2022 |
VLDB |
4.4301601e-05 |
| 9,194 |
MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud |
2024 |
VLDB |
4.3726269e-05 |
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| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 5,994 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
5.2367998e-05 |
| 9,972 |
End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure |
2026 |
CIDR |
4.1905499e-05 |
| 9,762 |
Adaptive data transformations for QaaS |
2025 |
CIDR |
4.2815042e-05 |
| 542 |
Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources |
2018 |
SIGMOD |
0.00020522627 |
| 2,244 |
Query Optimization in Microsoft SQL Server PDW |
2012 |
SIGMOD |
9.2095696e-05 |
| 3,623 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9017341e-05 |
| 6,683 |
Adaptive and Robust Query Execution for Lakehouses at Scale |
2024 |
VLDB |
4.9593505e-05 |
| 5,309 |
Continuous Cloud-Scale Query Optimization and Processing |
2013 |
VLDB |
5.5714729e-05 |
| 4,687 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
5.9915268e-05 |
| 7,203 |
Unified Query Optimization in the Fabric Data Warehouse |
2024 |
SIGMOD |
4.7968914e-05 |