Abstract
In the modern world, every technology and user generate a large amount of data. Each data carries value to some degree. Therefore, the concept of big data is actively developing because the idea of big data is to generate a new value. Addressing big data is an invocation and time-demanding job that needs a large computational infrastructure to ensure successful data processing, storage, and analysis. This report is intended to compare how one of the big data storage, Clickhouse, can replace the relational database, Oracle. This paper motivation is to obtain an understanding of the benefit and drawbacks of NoSQL database, in the case of Clickhouse to supporting a huge amount of data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Change history
01 November 2019
In the modern world, every technology and user generate a large amount of data. Each data carries value to some degree.
References
Laney, D.: 3-D Data Management: Controlling Data Volume, Velocity, and Variety. META Group Res Note 6, Stamford (2001)
Loukides, M.: What is Data Science. O’Reilly Media (2010)
Jacobs, A.: The pathologies of big data. Commun. ACM 8(52) (2009)
Cavanillas, M., Curry, E., Wahlster, W.: New Horizons for a Data-Driven Economy: A Roadmap for Usage and Exploitation of Big Data in Europe. Springer Open, Cham (2016)
TechAmerica Foundation.: Demystifying Big Data: A Practical Guide To Transforming The Business of Government. TechAmerica Foundation, Washington (2012)
Gandomi, A., Haider, M.: Beyond the hype: big data concepts, methods, and analytics. Int. J. Inf. Manag. 2(35), 137–144 (2015)
IBM Analytics. https://www.ibmbigdatahub.com/infographic/four-vs-big-data. Last accessed 05 Feb 2019
Bhadani, A., Jothimani, D.: Big data: challenges, opportunities and realities. In: Singh, M.K., Kumar, D.G. (eds.) Effective Big Data Management and Opportunities for Implementation 2016, pp. 1–24. IGI Global, Pennsylvania (2016)
Rajkumar, B., Rodrigo, C.A., Vahid, D.: Big Data Principles and Paradigms. Morgan Kaufmann, Cambridge (2016)
Sakr, S.: Big Data 2.0 Processing Systems: A Survey. Springer Publishing Company, Incorporated (2016)
Curry, E., Freitas, A., Ngonga, A.: D2.2.2 Final Version of Technical White Paper. Big Data Public Private Forum, pp. 2–8 (2014)
Lehmann, D., Fekete, D., Vossen, G.: Technology Selection for Big Data and Analytical Applications. European Research Center for Information Systems No. 27. (2016)
Cloudera Engineering Blog. https://blog.cloudera.com/blog/2014/09/getting-started-with-big-data-architecture/. Last accessed 04 Feb 2019
Rubin, A.: Column Store Database Benchmarks: MariaDB ColumnStore vs. Clickhouse vs. Apache Spark. https://www.percona.com/blog/2017/03/17/column-store-database-benchmarks-mariadb-columnstore-vs-clickhouse-vs-apache-spark/. Last accessed 17 Jan 2019
Yishan, L., Sathiamoorthy, M.: A performance comparison of SQL and NoSQL databases. In: Communications, Computers and Signal Processing. New Zealand (2013)
Altunity. ClickHouse for Time Series. https://www.altinity.com/blog/clickhouse-for-time-series. Last accessed 05 Jan 2019
Moniruzzaman, A., Hossain, S.: NoSQL database: new era of databases for big data analytics-classification, characteristics and comparison. Int. J. Database Theory Appl. 6(4) (2013)
Leventov, R.: Comparison of the Open Source OLAP Systems for Big Data: ClickHouse, Druid and Pinot. https://medium.com/@leventov/comparison-of-the-open-source-olap-systems-for-big-data-clickhouse-druid-and-pinot-8e042a5ed1c7. Last accessed 07 Jan 2019
Yandex. Distinctive Features of ClickHouse. https://clickhouse.yandex/docs/en/introduction/distinctive_features/. Last accessed 07 Jan 2019
Oracle. Database Limits. https://docs.oracle.com/cd/B28359_01/server.111/b28320/limits.htm#REFRN004. Last accessed 07 Jan 2019
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Imasheva, B., Azamat, N., Sidelkovskiy, A., Sidelkovskaya, A. (2020). The Practice of Moving to Big Data on the Case of the NoSQL Database, Clickhouse. In: Le Thi, H., Le, H., Pham Dinh, T. (eds) Optimization of Complex Systems: Theory, Models, Algorithms and Applications. WCGO 2019. Advances in Intelligent Systems and Computing, vol 991. Springer, Cham. https://doi.org/10.1007/978-3-030-21803-4_82
Download citation
DOI: https://doi.org/10.1007/978-3-030-21803-4_82
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-21802-7
Online ISBN: 978-3-030-21803-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)