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Efficiently Compiling Efficient Query Plans for Modern Hardware

Summary: Introduces LLVM-based compilation of queries into compact machine code optimized for locality and predictable branches, overcoming iterator/vectorization overheads. Integrated in HyPer, it approaches hand-written C++ performance with modest compilation time. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hbfb599b38b0c2b2f
Venue
VLDB
Year
2011
Pagerank
0.00056855599
Overall Rank
21 | 99.87%
DOI
10.14778/2002938.2002944

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{neumann_vldb11,
        title = {{Efficiently Compiling Efficient Query Plans for Modern Hardware}},
        author = {Neumann, Thomas},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {9},
        pages = {539--550},
        doi = {10.14778/2002938.2002944},
        url = {https://doi.org/10.14778/2002938.2002944},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 216 citing papers.

Rank Citing Paper Year Venue Pagerank
9,038 Bringing Cloud-Native Storage to SAP IQ 2021 SIGMOD 5.2331918e-05
9,063 One Loop Does Not Fit All 2015 SIGMOD 5.2286328e-05
9,148 In-depth Analysis of Continuous Subgraph Matching in a Common Delta Query Compilation Framework 2024 SIGMOD 5.2189946e-05
9,316 On-Demand State Separation for Cloud Data Warehousing 2022 VLDB 5.1958405e-05
9,321 Dynamic Speculative Optimizations for SQL Compilation in Apache Spark 2020 VLDB 5.1943472e-05
9,414 Provenance for SQL through Abstract Interpretation: Value-less, but Worthwhile 2015 VLDB 5.1815574e-05
9,472 Query Compilation Without Regrets 2024 SIGMOD 5.1711207e-05
9,553 Engineering High-Performance Database Engines 2014 VLDB 5.1585591e-05
9,566 Saving Private Hash Join 2025 VLDB 5.1571823e-05
9,600 Language-Agnostic Integrated Queries in a Managed Polyglot Runtime 2021 VLDB 5.1548991e-05
9,615 In-Browser Interactive SQL Analytics with Afterburner 2017 SIGMOD 5.1511784e-05
9,656 BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach 2023 SIGMOD 5.1453267e-05
9,684 The HANA Native Query Engine for Lakehouse Systems 2025 VLDB 5.1423628e-05
9,740 TreeToaster: Towards an IVM-Optimized Compiler 2021 SIGMOD 5.1349531e-05
9,748 PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development 2018 SIGMOD 5.1349531e-05
9,784 Memory Efficient Scheduling of Query Pipeline Execution 2022 CIDR 5.1285917e-05
9,794 Raqlet: Cross-Paradigm Compilation for Recursive Queries 2026 CIDR 5.1257999e-05
9,810 Scabbard: Single-Node Fault-Tolerant Stream Processing 2022 VLDB 5.1257999e-05
9,842 HiEngine: How to Architect a Cloud-Native Memory-Optimized Database Engine 2022 SIGMOD 5.1225854e-05
9,916 GeaFlow: A Graph Extended and Accelerated Dataflow System 2023 SIGMOD 5.1103839e-05
9,932 Optimization of Disjunctive Predicates for Main Memory Column Stores 2017 SIGMOD 5.1101087e-05
9,981 BIPie: Fast Selection and Aggregation on Encoded Data using Operator Specialization 2018 SIGMOD 5.1011277e-05
10,019 EinDecomp: Decomposition of Declaratively-Specified Machine Learning and Numerical Computations for Parallel Execution 2025 VLDB 5.0943606e-05
10,047 Tuplex: Robust, Efficient Analytics When Python Rules 2019 VLDB 5.091453e-05
10,140 How to Optimize SQL Queries? A Comparison Between Split, Holistic, and Hybrid Approaches 2025 VLDB 5.0742707e-05
10,174 Thriving in the No Man’s Land between Compilers and Databases 2019 CIDR 5.0681899e-05
10,193 Towards Unifying Query Interpretation and Compilation 2023 CIDR 5.0633497e-05
10,223 SQL Engines Excel at the Execution of Imperative Programs 2024 VLDB 5.0572221e-05
10,267 Darwin: Scale-In Stream Processing 2022 CIDR 5.0492285e-05
10,280 Chukonu: A Fully-Featured High-Performance Big Data Framework that Integrates a Native Compute Engine into Spark 2022 VLDB 5.0455234e-05
10,318 Out-of-order Execution of Database Queries 2020 VLDB 5.0367346e-05
10,416 Automating Database-Native Function Code Synthesis with LLMs 2026 SIGMOD 4.9793485e-05
10,448 EncoderForge: Generating Efficient SQL for Encoders in Machine Learning Inference Pipelines 2026 SIGMOD 4.9793485e-05
10,710 TurboLynx: Schemaless Graph Engine Strikes Back for General-Purpose Analytics 2026 VLDB 4.9793485e-05
10,723 Scalable GPU Acceleration of Scalar Functions in Analytical Databases: Compilation, Benchmarking, and Optimization 2026 VLDB 4.9793485e-05
10,741 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9793485e-05
10,801 PystachIO: Efficient Distributed GPU Query Processing with PyTorch over Fast Networks & Fast Storage 2026 VLDB 4.9793485e-05
10,842 The Data World Is Not Flat: Efficient Factorized Execution for Relational Systems 2026 VLDB 4.9793485e-05
10,858 Sema: A High-performance System for LLM-based Semantic Query Processing 2026 VLDB 4.9793485e-05
10,867 Nav-Index: A High-Performance, Adaptive Index for Shortest Path Queries in RDBMS 2026 VLDB 4.9793485e-05
10,881 One Pass to Parse Them All: Fused Parallel CSV Processing 2026 VLDB 4.9793485e-05
10,889 Rhyme Native: Efficient Code Generation for Structured and Semi-Structured Workloads 2026 VLDB 4.9793485e-05
10,901 Overlay Bitmap Encoding for Efficient Consumption of Apache Parquet Files 2026 VLDB 4.9793485e-05
10,914 FastCompose: Eliminating Compilation Cold Starts in Query Execution with Composition 2026 VLDB 4.9793485e-05
10,917 No Silver Bullet: Boosting GaussDB Performance on the 30TB TPC-H Workload 2026 VLDB 4.9793485e-05
10,923 TQP++: Bridging ML Compilers and Analytical Query Processing on GPUs 2026 VLDB 4.9793485e-05
10,927 A Decade of Apache Spark Structured Streaming: How We Evolved The Architecture To Meet Real-World Needs 2026 VLDB 4.9793485e-05
10,932 IMLane: Composable Framework for Efficient AI Function Execution in Database Engine 2026 VLDB 4.9793485e-05
10,946 Why We Created Yet Another Memory Framework: Understanding MGA’s Role in Next-Gen Database Systems 2026 VLDB 4.9793485e-05
10,973 Demonstrating GenDB: Instance-Optimized and Customized Query Processing Code Generation via LLM Agents 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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