Big Database Stores A review on various big data datastores

被引:0
|
作者
George, Koshy [1 ]
Mathew, Tessy [1 ]
机构
[1] Mar Baselios Coll Engn & Technol, Dept Comp Sci & Engn, Trivandrum, Kerala, India
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this age where there is a massive explosion in the data in our surroundings, the traditional way of actually storing and processing the data is no longer feasible. Moreover, the unstructured data that is present cannot be processed by the conventional ways. With the emergence of this data explosion also known as Big Data, a lot of importance has given to actually process and more importantly analyze the data to get the best results being in terms of decision making or predicting the future evens based on the past data at hand. The traditional SQLs have become impractical to process the latest data inflow as it lacks the structure, elasticity requirements and the high scalability. NoSQL or what can be known as Not Only SQL actually help find by a way out of the traditional approach and help process the unstructured data. For Big Data to function at its best, it needs the help of specialized databases that help in storing and processing data when needed. There are 4 main categories of the Datastores used in Big Data namely Key-Value Pair Datastore, Column Oriented Datastore, Document Oriented Datastore and Graph Datastores.
引用
收藏
页码:567 / 573
页数:7
相关论文
共 50 条
  • [1] Data (with Big Data and Database Semantics)
    Hjorland, Birger
    KNOWLEDGE ORGANIZATION, 2018, 45 (08): : 685 - 708
  • [2] SURVEY OF DATA PARTITIONING ALGORITHMS FOR BIG DATA STORES
    Phansalkar, Shraddha
    Ahirrao, Swati
    2016 FOURTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING (PDGC), 2016, : 163 - 168
  • [3] Big Data Approach and its applications in Various Fields: Review
    Rabhi, Loubna
    Falih, Noureddine
    Afraites, Abdlekbir
    Bouikhalene, Belaid
    16TH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS AND PERVASIVE COMPUTING (MOBISPC 2019),THE 14TH INTERNATIONAL CONFERENCE ON FUTURE NETWORKS AND COMMUNICATIONS (FNC-2019),THE 9TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY, 2019, 155 : 599 - 605
  • [4] Big Data: A Review
    Sagiroglu, Seref
    Sinanc, Duygu
    PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON COLLABORATION TECHNOLOGIES AND SYSTEMS (CTS), 2013, : 42 - 47
  • [5] The Review of Big Data
    Shi, Chunhe
    Wu, Chengdong
    Han, Xiaowei
    Li, Zhen
    Xie, Yinghong
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON ELECTRONIC, MECHANICAL, INFORMATION AND MANAGEMENT SOCIETY (EMIM), 2016, 40 : 108 - 112
  • [6] Geospatial Big Data or Big Geospatial Data: A Bibliometric Review
    Ndu, Chidinma Godsgood
    Shoko, Moreblessings
    SOUTH AFRICAN JOURNAL OF GEOMATICS, 2024, 13 (01): : 158 - 171
  • [7] QUEST Database for Tokamak Big Data
    Hasegawa, Makoto
    Higashijima, Aki
    Niiya, Ichiro
    Hanada, Kazuaki
    Idei, Hiroshi
    Ido, Takeshi
    Ikezoe, Ryuya
    Onchi, Takumi
    Kuroda, Kengo
    Sakurai, Daisuke
    Plasma and Fusion Research, 2023, 18
  • [8] QUEST Database for Tokamak Big Data
    Hasegawa, Makoto
    Higashijima, Aki
    Niiya, Ichiro
    Hanada, Kazuaki
    Idei, Hiroshi
    Ido, Takeshi
    Ikezoe, Ryuya
    Onchi, Takumi
    Kuroda, Kengo
    Sakurai, Daisuke
    PLASMA AND FUSION RESEARCH, 2023, 18
  • [9] MiniCrypt: Reconciling Encryption and Compression for Big Data Stores
    Zheng, Wenting
    Li, Frank
    Popa, Raluca Ada
    Stoica, Ion
    Agarwal, Rachit
    PROCEEDINGS OF THE TWELFTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS 2017), 2017, : 191 - 204
  • [10] How big is a database versus how is a database big
    Jacso, Peter
    ONLINE INFORMATION REVIEW, 2007, 31 (04) : 533 - 536