Totally Ordered Replication for Massive Scale Key-Value Stores

被引:0
|
作者
Ribeiro, Jose [1 ]
Machado, Nuno [1 ]
Maia, Francisco [1 ]
Matos, Miguel [2 ]
机构
[1] Univ Minho, HASLab, INESC TEC, Braga, Portugal
[2] Univ Lisbon, Inst Super Tecn, INESC ID, Lisbon, Portugal
关键词
D O I
10.1007/978-3-319-93767-0_5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Scalability is one of the most relevant features of today's data management systems. In order to achieve high scalability and availability, recent distributed key-value stores refrain from costly replica coordination when processing requests. However, these systems typically do not perform well under churn. In this paper, we propose DataFlagons, a large-scale key-value store that integrates epidemic dissemination with a probabilistic total order broadcast algorithm. By ensuring that all replicas process requests in the same order, DataFlagons provides probabilistic strong data consistency while achieving high scalability and robustness under churn.
引用
收藏
页码:58 / 74
页数:17
相关论文
共 50 条
  • [41] COBRA: Making Transactional Key-Value Stores Verifiably Serializable
    Tan, Cheng
    Zhao, Changgeng
    Mu, Shuai
    Walfish, Michael
    PROCEEDINGS OF THE 14TH USENIX SYMPOSIUM ON OPERATING SYSTEMS DESIGN AND IMPLEMENTATION (OSDI '20), 2020, : 63 - 80
  • [42] Chapar: Certified Causally Consistent Distributed Key-Value Stores
    Lesani, Mohsen
    Bell, Christian J.
    Chlipala, Adam
    ACM SIGPLAN NOTICES, 2016, 51 (01) : 357 - 370
  • [43] An adaptive replica placement approach for distributed key-value stores
    Costa Filho, Jose S.
    Cavalcante, Denis M.
    Moreira, Leonardo O.
    Machado, Javam C.
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2020, 32 (11):
  • [44] Ontology-Mediated Query Answering for Key-Value Stores
    Bienvenu, Meghyn
    Bourhis, Pierre
    Mugnier, Marie-Laure
    Tison, Sophie
    Ulliana, Federico
    PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 844 - 851
  • [45] SplinterDB: Closing the Bandwidth Gap for NVMe Key-Value Stores
    Conway, Alex
    Gupta, Abhishek
    Chidambaran, Vijay
    Farach-Colton, Martin
    Spillane, Rick
    Tai, Amy
    Johnson, Rob
    PROCEEDINGS OF THE 2020 USENIX ANNUAL TECHNICAL CONFERENCE, 2020, : 49 - 63
  • [46] GeoWave: Utilizing Distributed Key-Value Stores for Multidimensional Data
    Whitby, Michael A.
    Fecher, Rich
    Bennight, Chris
    ADVANCES IN SPATIAL AND TEMPORAL DATABASES, SSTD 2017, 2017, 10411 : 105 - 122
  • [47] Compressed Incremental Checkpointing for Efficient Replicated Key-Value Stores
    Guler, Berkin
    Ozkasap, Oznur
    2017 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2017, : 76 - 81
  • [48] Oblivious Key-Value Stores and Amplification for Private Set Intersection
    Garimella, Gayathri
    Pinkas, Benny
    Rosulek, Mike
    Ni Trieu
    Yanai, Avishay
    ADVANCES IN CRYPTOLOGY - CRYPTO 2021, PT II, 2021, 12826 : 395 - 425
  • [49] Chisel: Reshaping Queries to Trim Latency in Key-Value Stores
    Birke, Robert
    Perez, Juan E.
    Ben Mokhtar, Sonia
    Rameshan, Navaneeth
    Chen, Lydia Y.
    2019 IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING (ICAC 2019), 2019, : 42 - 51
  • [50] BigSecret: A Secure Data Management Framework for Key-Value Stores
    Pattuk, Erman
    Kantarcioglu, Murat
    Khadilkar, Vaibhav
    Ulusoy, Huseyin
    Mehrotra, Sharad
    2013 IEEE SIXTH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD 2013), 2013, : 147 - 154