1 |
LI G, ZHANG C. HTAP databases: What is new and what is next[C]// Proceedings of the 2022 International Conference on Management of Data. 2022: 2483-2488.
|
2 |
胡梓锐, 翁思扬, 王清帅, 等. HTAP数据库系统数据共享模型和优化策略 [J]. 软件学报, 2023. DOI: 10.13328/j.cnki.jos.006901.
|
3 |
LYU Z, ZHANG H H, XIONG G, et al. Greenplum: A hybrid database for transactional and analytical workloads [C]// Proceedings of the 2021 International Conference on Management of Data. 2021: 2530-2542.
|
4 |
HUANG D, LIU Q, CUI Q, et al.. TiDB: A Raft-based HTAP database. Proceedings of the VLDB Endowment, 2020, 13 (12): 3072- 3084.
|
5 |
WANG J Y, LI T L, SONG H Z, et al.. PolarDB-IMCI: A cloud-native HTAP database system at Alibaba. Proceedings of the ACM on Management of Data, 2023, 1 (2): 199.
|
6 |
CAO W, LIU Z J, WANG P, et al.. PolarFS: An ultra-low latency and failure resilient distributed file system for shared storage cloud database. Proceedings of the VLDB Endowment, 2018, 11 (12): 1849- 1862.
|
7 |
YANG Z K, YANG C H, HAN F S, et al.. OceanBase: A 707 million tpmC distributed relational database system. Proceedings of the VLDB Endowment, 2022, 15 (12): 3385- 3397.
|
8 |
VERBITSKI A, GUPTA A, SAHA D, et al. Amazon aurora: Design considerations for high throughput cloud-native relational databases [C]// Proceedings of the 2017 ACM International Conference on Management of Data. 2017: 1041-1052.
|
9 |
VERBITSKI A, GUPTA A, SAHA D, et al. Amazon aurora: On avoiding distributed consensus for I/Os, commits, and membership changes [C]// Proceedings of the 2018 International Conference on Management of Data. 2018: 789-796.
|
10 |
YANG J C, RAE I, XU J, et al.. F1 Lightning: HTAP as a service. Proceedings of the VLDB Endowment, 2020, 13 (12): 3313- 3325.
|
11 |
张超, 李国良, 冯建华, 等.. HTAP数据库关键技术综述. 软件学报, 2023, 34 (2): 761- 785.
|
12 |
ÖZCAN F, TIAN Y Y, TÖZÜN P. Hybrid transactional/analytical processing: A survey [C]// Proceedings of the 2017 ACM International Conference on Management of Data. 2017: 1771-1775.
|
13 |
KRASKA T, HENTSCHEL M, ALONSO G, et al.. Consistency rationing in the cloud: Pay only when it matters. Proceedings of the VLDB Endowment, 2009, 2 (1): 253- 264.
|
14 |
CHEN J, DING Y, LIU Y, et al.. ByteHTAP: Bytedance’s HTAP system with high data freshness and strong data consistency. Proceedings of the VLDB Endowment, 2022, 15 (12): 3411- 3424.
|
15 |
LU Y, LU Y, JIANG H. Adaptive consistency guarantees for large-scale replicated services [C]// Proceedings of the 2008 International Conference on Networking, Architecture, and Storage. 2008: 89-96.
|
16 |
YU H, VAHDAT A.. Design and evaluation of a conit-based continuous consistency model for replicated services. ACM Transactions on Computer Systems, 2002, 20 (3): 239- 282.
|
17 |
GAO L, DAHLIN M, NAYATE A, et al. Application specific data replication for edge services [C]// Proceedings of the 12th International Conference on World Wide Web. 2003: 449-460.
|
18 |
杨志丰. 分布式存储系统的一致性是什么? [EB/OL]. (2022-06-27)[2023-05-11]. https://zhuanlan.zhihu.com/p/34656939.
|
19 |
YAN H, SHAWN T. 使用TiDB读取TiFlash [EB/OL]. (2022-12-06)[2023-06-04]. https://docs.pingcap.com/zh/tidb/stable/use-tidb-to-read-tiflash.
|
20 |
CAO W, LI F, HUANG G, et al. PolarDB-X: An elastic distributed relational database for cloud-native applications [C]// Proceedings of the 2022 IEEE 38th International Conference on Data Engineering. 2022: 2859-2872.
|
21 |
SHEN S, CHEN R, CHEN H, et al. Retrofitting high availability mechanism to tame hybrid transaction/analytical processing [C]// Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation. 2021: 219-238.
|