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High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance

Summary: Adaptive materialization turns in-memory hash operators into spill-friendly OOM operators without sacrificing in-memory speed. Self-regulating compression optimizes spilling throughput on NVMe arrays, enabling Spilly to match in-memory performance while handling large out-of-memory workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
he4ccf7f62032a771
Venue
SIGMOD
Year
2024
Pagerank
4.9793485e-05
Overall Rank
11,542 | 22.40%
DOI
10.1145/3698813

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{kuschewski_sigmod24,
        title = {{High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance}},
        author = {Kuschewski, Maximilian and Giceva, Jana and Neumann, Thomas and Leis, Viktor},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3698813},
        url = {https://dl.acm.org/doi/10.1145/3698813},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
9,793 Declarative Memory Services 2026 CIDR 5.1257999e-05
10,725 How to Write to SSDs 2026 VLDB 4.9793485e-05
10,833 BtrLog: Low-Latency Logging for Cloud Database Systems 2026 VLDB 4.9793485e-05
11,037 Future-Proof Data Systems 2026 VLDB 4.9793485e-05
11,344 Towards Designing Future-Proof Data Processing Systems 2025 VLDB 4.9793485e-05
11,433 CloudGlide: Deconstructing the Landscape of Cloud-Based Analytics 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 43 of 43 cited papers.

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

Rank Cited Paper Year Venue Pagerank
7 Implementation Techniques For Main Memory Database Systems 1984 SIGMOD 0.00081992507
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
27 Database Architecture Optimized for the New Bottleneck: Memory Access 1999 VLDB 0.0005158963
48 Weaving Relations for Cache Performance 2001 VLDB 0.00043805923
70 The End of an Architectural Era (It’s Time for a Complete Rewrite) 2007 VLDB 0.00037859131
71 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00037720227
110 DBMSs On A Modern Processor: Where Does Time Go? 1999 VLDB 0.00032700879
157 OLTP Through the Looking Glass, and What We Found There 2008 SIGMOD 0.00028317906
163 DB2 with BLU Acceleration: So Much More than Just a Column Store 2013 VLDB 0.0002749118
170 High-Performance Concurrency Control Mechanisms for Main-Memory Databases 2012 VLDB 0.0002705961
215 Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age 2014 SIGMOD 0.00024598661
361 Design and Evaluation of Main Memory Hash Join Algorithms for Multi-core CPUs 2011 SIGMOD 0.00020006406
373 Umbra: A Disk-Based System with In-Memory Performance 2020 CIDR 0.00019711632
605 Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask 2018 VLDB 0.00015647561
626 Adaptive Aggregation on Chip Multiprocessors 2007 VLDB 0.00015473276
853 Hash-Partitioned Join Method Using Dynamic Destaging Strategy 1988 VLDB 0.00013444911
1,059 Accelerating Relational Databases by Leveraging Remote Memory and RDMA 2016 SIGMOD 0.00012224884
1,116 A Comprehensive Study of Main-Memory Partitioning and its Application to Large-Scale Comparison- and Radix-Sort 2014 SIGMOD 0.00011962096
1,266 An Experimental Comparison of Thirteen Relational Equi-Joins in Main Memory 2016 SIGMOD 0.00011269175
1,484 Query Processing Techniques for Solid State Drives 2009 SIGMOD 0.00010535051
1,802 Hash joins and hash teams in Microsoft SQL Server 1998 VLDB 9.6081518e-05
2,137 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 8.9777553e-05
2,245 Cache-Efficient Aggregation: Hashing Is Sorting 2015 SIGMOD 8.7649358e-05
2,314 BtrBlocks: Efficient Columnar Compression for Data Lakes 2023 SIGMOD 8.6533171e-05
2,818 To Partition, or Not to Partition, That is the Join Question in a Real System 2021 SIGMOD 7.9739791e-05
2,839 Turbocharging DBMS Buffer Pool Using SSDs 2011 SIGMOD 7.9506131e-05
2,877 Exploiting Directly-Attached NVMe Arrays in DBMS 2020 CIDR 7.9181223e-05
2,920 What Modern NVMe Storage Can Do, And How To Exploit It: High-Performance I/O for High-Performance Storage Engines 2023 VLDB 7.8540089e-05
3,100 Micro Adaptivity in Vectorwise 2013 SIGMOD 7.6505054e-05
3,316 Cloud Analytics Benchmark 2023 VLDB 7.4373161e-05
3,427 Efficient Processing of Window Functions in Analytical SQL Queries 2015 VLDB 7.3082914e-05
3,855 Making Updates Disk-I/O Friendly Using SSDs 2013 VLDB 6.9694249e-05
4,034 Exploiting Cloud Object Storage for High-Performance Analytics 2023 VLDB 6.8393244e-05
4,243 The Art of Latency Hiding in Modern Database Engines 2024 VLDB 6.7069789e-05
4,296 Redy: Remote Dynamic Memory Cache 2022 VLDB 6.6805238e-05
5,179 On the Surprising Difficulty of Simple Things: the Case of Radix Partitioning 2015 VLDB 6.2408516e-05
5,251 Data Management Over Flash Memory 2011 SIGMOD 6.2090582e-05
5,637 MaSM: Efficient Online Updates in Data Warehouses 2011 SIGMOD 6.0569403e-05
6,489 HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics 2023 CIDR 5.7676507e-05
7,923 NOCAP: Near-Optimal Correlation-Aware Partitioning Joins 2023 SIGMOD 5.4260253e-05
7,926 Design Trade-offs for a Robust Dynamic Hybrid Hash Join 2022 VLDB 5.425615e-05
10,243 The Need for a New I/O Model 2021 CIDR 5.0525742e-05
10,248 Accelerating Analytics with Dynamic In-Memory Expressions 2016 VLDB 5.0525742e-05
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