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HiEngine: How to Architect a Cloud-Native Memory-Optimized Database Engine

Summary: HiEngine introduces a hierarchical, cloud-native in-memory engine that combines main-memory performance with compute-side reliable persistence and compatibility with disk-centric systems. Integrated into GaussDB, it coexists with disk engines and achieves up to 7.5× speedups. (summarized by gpt-5.6-luna on Jul 21 2026)

Paper ID
hcc3cb1f10b1eb151
Venue
SIGMOD
Year
2022
Pagerank
5.1225854e-05
Overall Rank
9,842 | 33.83%
DOI
10.1145/3514221.3526043

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{ma_sigmod22,
        title = {{HiEngine: How to Architect a Cloud-Native Memory-Optimized Database Engine}},
        author = {Ma, Yunus and Xie, Siphrey and Zhong, Henry and Lee, Leon and Lv, King},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526043},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526043},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
8,082 Krypton: Real-time Serving and Analytical SQL Engine at ByteDance 2023 VLDB 5.3942942e-05
8,243 Index Checkpoints for Instant Recovery in In-Memory Database Systems 2022 VLDB 5.3701805e-05
11,102 Boosting OLTP Performance with Per-Page Logging on NVDIMM 2025 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 23 of 23 cited papers.

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

Rank Cited Paper Year Venue Pagerank
21 Efficiently Compiling Efficient Query Plans for Modern Hardware 2011 VLDB 0.00056855599
35 Hekaton: SQL Server’s Memory-Optimized OLTP Engine 2013 SIGMOD 0.00048001919
63 Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases 2017 SIGMOD 0.00038531147
70 The End of an Architectural Era (It’s Time for a Complete Rewrite) 2007 VLDB 0.00037859131
170 High-Performance Concurrency Control Mechanisms for Main-Memory Databases 2012 VLDB 0.0002705961
237 Serializable Isolation for Snapshot Databases 2008 SIGMOD 0.00023660039
542 FOEDUS: OLTP Engine for a Thousand Cores and NVRAM 2015 SIGMOD 0.0001665543
543 Socrates: The New SQL Server in the Cloud 2019 SIGMOD 0.0001663263
614 Scalable Logging through Emerging Non-Volatile Memory 2014 VLDB 0.0001556755
636 ERMIA: Fast Memory-Optimized Database System for Heterogeneous Workloads 2016 SIGMOD 0.00015360975
786 Cicada: Dependably Fast Multi-Core In-Memory Transactions 2017 SIGMOD 0.00013988699
872 An Empirical Evaluation of In-Memory Multi-Version Concurrency Control 2017 VLDB 0.00013342029
1,026 Aether: A Scalable Approach to Logging 2010 VLDB 0.00012423267
1,083 High Performance Transactions in Deuteronomy 2015 CIDR 0.00012113053
1,339 The End of a Myth: Distributed Transactions Can Scale 2017 VLDB 0.00010975458
2,394 What Are We Doing With Our Lives? Nobody Cares About Our Concurrency Control Research 2017 SIGMOD 8.5295579e-05
2,671 Taurus Database: How to be Fast, Available, and Frugal in the Cloud 2020 SIGMOD 8.15025e-05
2,951 Constant Time Recovery in Azure SQL Database 2019 VLDB 7.8166642e-05
3,062 Opportunities for Optimism in Contended Main-Memory Multicore Transactions 2020 VLDB 7.6920087e-05
3,676 Fast General Distributed Transactions with Opacity 2019 SIGMOD 7.1063551e-05
3,855 Making Updates Disk-I/O Friendly Using SSDs 2013 VLDB 6.9694249e-05
6,923 Industrial-Strength OLTP Using Main Memory and Many Cores 2020 VLDB 5.643245e-05
8,243 Index Checkpoints for Instant Recovery in In-Memory Database Systems 2022 VLDB 5.3701805e-05
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