A systematic review of in-memory database over multi-tenancy

The significant cost and time are essential to obtain a comprehensive response, the response time to a query across a peer-to-peer database is one of the most challenging issues. This is particularly exact when dealing with large-scale data processing, where the traditional approach of processing da...

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Bibliographic Details
Published in:International journal of electrical and computer engineering (Malacca, Malacca) Vol. 14; no. 2; p. 1720
Main Authors: Shah, Arpita, Bhatt, Nikita
Format: Journal Article
Language:English
Published: 01.04.2024
ISSN:2088-8708, 2722-2578
Online Access:Get full text
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Summary:The significant cost and time are essential to obtain a comprehensive response, the response time to a query across a peer-to-peer database is one of the most challenging issues. This is particularly exact when dealing with large-scale data processing, where the traditional approach of processing data on a single machine may not be sufficient. The need for a scalable, reliable, and secure data processing system is becoming increasingly important. Managing a single in-memory database instance for multiple tenants is often easier than managing separate databases for each tenant. The research work is focused on scalability with multi-tenancy and more efficiency with a faster querying performance using in-memory database approach. We compare the performance of a row-oriented approach and column-oriented approach on our benchmark human resources (HR) schema using Oracle TimesTen in-memory database. Also, we captured some of the key advantages on optimization dimension(s) are the traditional approach, late-materialization, compression and invisible join on column-store (c-store) and row-base. When compression and late materialization are enabled in a query set; it improves the overall performance of query sets. In particular, the paper aims to elucidate the motivations behind multi-tenant application requirements concerning the database engine and highlight major designs over in-memory database for the tenancy approach on cloud.
ISSN:2088-8708
2722-2578
DOI:10.11591/ijece.v14i2.pp1720-1729