Welcome to the InfoSci Platform
Significance of In-Memory Computing for Real-Time Big Data Analytics

Significance of In-Memory Computing for Real-Time Big Data Analytics

Ganesh Chandra Deka
Copyright: © 2014 |Pages: 18
ISBN13: 9781466658646|ISBN10: 1466658649|EISBN13: 9781466658653
DOI: 10.4018/978-1-4666-5864-6.ch014
Cite Chapter Cite Chapter

MLA

Deka, Ganesh Chandra. "Significance of In-Memory Computing for Real-Time Big Data Analytics." Handbook of Research on Cloud Infrastructures for Big Data Analytics, edited by Pethuru Raj and Ganesh Chandra Deka, IGI Global, 2014, pp. 352-369. https://doi.org/10.4018/978-1-4666-5864-6.ch014

APA

Deka, G. C. (2014). Significance of In-Memory Computing for Real-Time Big Data Analytics. In P. Raj & G. Deka (Eds.), Handbook of Research on Cloud Infrastructures for Big Data Analytics (pp. 352-369). IGI Global. https://doi.org/10.4018/978-1-4666-5864-6.ch014

Chicago

Deka, Ganesh Chandra. "Significance of In-Memory Computing for Real-Time Big Data Analytics." In Handbook of Research on Cloud Infrastructures for Big Data Analytics, edited by Pethuru Raj and Ganesh Chandra Deka, 352-369. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-5864-6.ch014

Export Reference

Mendeley
Favorite

Abstract

Cloud computing provides online access of users’ data anytime, anywhere, any application, and any device. Due to the slower read/write operation of conventional disk resident databases, they are incapable of meeting the real-time, Online Transaction Processing (OLTP) requirements of cloud-based application, specifically e-Commerce application. Since In-Memory database store the database in RAM, In-Memory databases drastically reduce the read/write times leading to high throughput of a cloud-based OLTP systems. This chapter discusses In-Memory real time analytics.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.