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HTAP Databases: What is New and What is Next
Summary: Comprehensive HTAP survey: taxonomy of systems by storage architectures and mixed OLTP/OLAP designs; analyzes transaction processing, analytics, data synchronization, and resource scheduling. Includes HTAP benchmarks and outlines open challenges.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
6467
Venue
SIGMOD
Year
2022
Pagerank
7.1449267e-05
Overall Rank
3,762 | 74.20%
DOI
10.1145/3514221.3522565
Incoming Non-self Citations Over Time
BibTeX Citation
Copy BibTeX
@inproceedings{li_sigmod22,
title = {{HTAP Databases: What is New and What is Next}},
author = {Li, Guoliang and Zhang, Chao},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3522565},
url = {https://dl.acm.org/doi/10.1145/3514221.3522565},
year = {2022}
}
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18
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2016
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0.00059284255
38
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2013
SIGMOD
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154
Neo: A Learned Query Optimizer
2019
VLDB
0.00028726181
165
DB2 with BLU Acceleration: So Much More than Just a Column Store
2013
VLDB
0.00027693424
233
Fast Serializable Multi-Version Concurrency Control for Main-Memory Database Systems
2015
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0.00023815642
271
TiDB: A Raft-based HTAP Database
2020
VLDB
0.00022703024
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An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning
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QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning
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575
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1,199
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2016
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1,312
Hybrid Transactional/Analytical Processing: A Survey
2017
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0.00011193166
1,692
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2015
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9.9979924e-05
2,583
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2019
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8.0175489e-05
2,888
AI Meets Database: AI4DB and DB4AI
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2,922
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3,662
openGauss: An Autonomous Database System
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2017
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