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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
7048
Venue
SIGMOD
Year
2024
Pagerank
5.093636e-05
Overall Rank
11,200 | 23.16%
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 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
10,127 Declarative Memory Services 2026 CIDR 5.093636e-05
10,543 How to Write to SSDs 2026 VLDB 5.093636e-05
10,957 Towards Designing Future-Proof Data Processing Systems 2025 VLDB 5.093636e-05
11,076 CloudGlide: Deconstructing the Landscape of Cloud-Based Analytics 2025 VLDB 5.093636e-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 0.00083340894
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
29 Database Architecture Optimized for the New Bottleneck: Memory Access 1999 VLDB 0.00052093615
49 Weaving Relations for Cache Performance 2001 VLDB 0.00043781096
68 The End of an Architectural Era (It’s Time for a Complete Rewrite) 2007 VLDB 0.00038446206
103 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00034161428
109 DBMSs On A Modern Processor: Where Does Time Go? 1999 VLDB 0.000331207
157 OLTP Through the Looking Glass, and What We Found There 2008 SIGMOD 0.0002863588
165 DB2 with BLU Acceleration: So Much More than Just a Column Store 2013 VLDB 0.00027693424
172 High-Performance Concurrency Control Mechanisms for Main-Memory Databases 2012 VLDB 0.00027281663
241 Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age 2014 SIGMOD 0.00023654664
360 Design and Evaluation of Main Memory Hash Join Algorithms for Multi-core CPUs 2011 SIGMOD 0.00020182846
422 Umbra: A Disk-Based System with In-Memory Performance 2020 CIDR 0.00018732744
632 Adaptive Aggregation on Chip Multiprocessors 2007 VLDB 0.00015575286
649 Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask 2018 VLDB 0.00015320656
844 Hash-Partitioned Join Method Using Dynamic Destaging Strategy 1988 VLDB 0.00013664056
1,117 Accelerating Relational Databases by Leveraging Remote Memory and RDMA 2016 SIGMOD 0.00012108907
1,177 A Comprehensive Study of Main-Memory Partitioning and its Application to Large-Scale Comparison- and Radix-Sort 2014 SIGMOD 0.00011808761
1,265 An Experimental Comparison of Thirteen Relational Equi-Joins in Main Memory 2016 SIGMOD 0.00011415709
1,455 Query Processing Techniques for Solid State Drives 2009 SIGMOD 0.00010733981
1,809 Hash joins and hash teams in Microsoft SQL Server 1998 VLDB 9.7034998e-05
2,156 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 9.0635624e-05
2,250 Cache-Efficient Aggregation: Hashing Is Sorting 2015 SIGMOD 8.8694486e-05
2,788 BtrBlocks: Efficient Columnar Compression for Data Lakes 2023 SIGMOD 8.1205155e-05
2,828 Exploiting Directly-Attached NVMe Arrays in DBMS 2020 CIDR 8.0803679e-05
2,962 To Partition, or Not to Partition, That is the Join Question in a Real System 2021 SIGMOD 7.9170451e-05
3,001 What Modern NVMe Storage Can Do, And How To Exploit It: High-Performance I/O for High-Performance Storage Engines 2023 VLDB 7.8673493e-05
3,095 Turbocharging DBMS Buffer Pool Using SSDs 2011 SIGMOD 7.7641876e-05
3,195 Micro Adaptivity in Vectorwise 2013 SIGMOD 7.6481177e-05
3,673 Efficient Processing of Window Functions in Analytical SQL Queries 2015 VLDB 7.2113383e-05
3,808 Making Updates Disk-I/O Friendly Using SSDs 2013 VLDB 7.1083217e-05
3,838 Cloud Analytics Benchmark 2023 VLDB 7.0823175e-05
4,103 Exploiting Cloud Object Storage for High-Performance Analytics 2023 VLDB 6.8993506e-05
4,440 The Art of Latency Hiding in Modern Database Engines 2024 VLDB 6.7049797e-05
4,677 Redy: Remote Dynamic Memory Cache 2022 VLDB 6.5698961e-05
5,094 On the Surprising Difficulty of Simple Things: the Case of Radix Partitioning 2015 VLDB 6.3657592e-05
5,144 Data Management Over Flash Memory 2011 SIGMOD 6.3473454e-05
5,564 MaSM: Efficient Online Updates in Data Warehouses 2011 SIGMOD 6.1716245e-05
6,487 HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics 2023 CIDR 5.8651793e-05
7,760 NOCAP: Near-Optimal Correlation-Aware Partitioning Joins 2023 SIGMOD 5.5505651e-05
7,800 Design Trade-offs for a Robust Dynamic Hybrid Hash Join 2022 VLDB 5.5420279e-05
10,048 The Need for a New I/O Model 2021 CIDR 5.1685424e-05
10,053 Accelerating Analytics with Dynamic In-Memory Expressions 2016 VLDB 5.1685424e-05
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