SQL Versus NoSQL Databases to Assess Their Appropriateness for Big Data Application

Kausar, Mohammad Abu; Nasar, Mohammad

doi:10.2174/2213275912666191028111632

Cited by 9 publications

(6 citation statements)

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“…In contrast, for unstructured or semi-structured data, such as user interaction logs and product reviews, this research relies on NoSQL databases. NoSQL databases, with their more flexible nature and high scalability, are ideal for handling large data that varies in format and structure [20] [21]. NoSQL's ability to store various types of data without schema still allows for more dynamic and heterogeneous data handling.…”

Section: Data Modelingmentioning

confidence: 99%

Analysis of E-Commerce Purchase Patterns Using Big Data: An Integrative Approach to Understanding Consumer Behavior

Caroline,

Yuswardi,

Rofi'i

2023

ijsecs

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This research undertakes a meticulous examination of the Indonesian e-commerce industry, aiming to unravel the intricate patterns governing consumer behavior within this rapidly evolving digital landscape. Employing an extensive dataset and cutting-edge data analysis methodologies, this study discerns pivotal trends that have engendered transformative shifts in Indonesia's e-commerce sector. A conspicuous trend uncovered is the escalating reliance on instant messaging platforms and social media conduits for e-commerce transactions. This pronounced transition underscores the remarkable adaptability of businesses to the digital milieu, thereby accentuating the significance of a digitally oriented business paradigm. Furthermore, this research brings to light the prevailing predilection among non-formal e-commerce enterprises, whose revenues predominantly dwell below the IDR 300 million threshold. Notably, the Cash on Delivery (COD) method remains the preeminent payment mechanism. These observations illuminate the structural underpinnings of the market and consumer payment proclivities, thereby exerting a discernible influence on pricing strategies and payment processing mechanisms adopted by enterprises. Moreover, the study delves into the transformative effects of the COVID-19 pandemic, which have expedited the digital metamorphosis of both consumers and e-commerce enterprises. This acceleration has ushered in a new epoch characterized by novel opportunities and concomitant challenges within the e-commerce domain. In summation, this research furnishes a multidimensional and academically rigorous perspective on the Indonesian e-commerce landscape, furnishing actionable insights indispensable for businesses and policymakers alike. The comprehension of these evolving trends is indispensable for strategic formulation and policy calibration, enabling adept navigation of the dynamic e-commerce milieu.

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Section: Data Modelingmentioning

confidence: 99%

Analysis of E-Commerce Purchase Patterns Using Big Data: An Integrative Approach to Understanding Consumer Behavior

Caroline,

Yuswardi,

Rofi'i

2023

ijsecs

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“…On one hand, relational databases deliver accuracy and redundancy by following the ACID properties. On the other hand, non-relational databases support large and distributed datasets with frequently changing schemas providing better performance and flexibility [73], which makes them particularly attractive for industries requiring highperformance analytics capabilities and distributed large data scalability [49]. Currently, efforts are being made to merge the two database systems to offer the best of both worlds [45,92], where, for example, a hybrid model would provide the flexibility that is prevented by the rigid relational database framework [54].…”

Section: Data Storage Costs and Cloud Implementationmentioning

confidence: 99%

Cloud based evaluation of databases for stock market data

Singh

Martyr

Medland³

et al. 2022

J Cloud Comp

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About fifty years ago, the world’s first fully automated system for trading securities was introduced by Instinet in the US. Since then the world of trading has been revolutionised by the introduction of electronic markets and automatic order execution. Nowadays, financial institutions exploit the associated flow of daily data using more and more advanced analytics to gain valuable insight on the markets and inform their investment decisions. In particular, time series of Open High Low Close prices and Volume data are of special interest as they allow identifying trading patterns useful for forecasting both stock prices and volumes. Traditionally, relational databases have been used to store this data; however, the ever-growing volume of this data, the adoption of the hybrid cloud model, and the availability of novel non-relational databases which claim to be more scalable and fault tolerant raise the question whether relational databases are still the most appropriate. In this study, we define a set of criteria to evaluate performance of a variety of databases on a hybrid cloud environment. There, we conduct experiments using standard and custom workloads. Results show that migration to a MongoDB database would be most beneficial in terms of cost, storage space, and throughput. In addition, organisations wishing to take advantage of autoscaling and the maintenance power of the cloud should opt for a cloud native solution.

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“…Textual data is unstructured with Big Data, Internet organizations and enterprises are using NoSQL more. Simplicity, horizontal scalability, and availability management are benefits [2]. NoSQL databases are viewed as a potential alternative to relational databases because their schema-free data format can handle huge volumes of structured, semistructured, and unstructured data.…”

Section: Introductionmentioning

confidence: 99%

A State of Art Survey for Big Data Processing and NoSQL Database Architecture

ALI¹,

NAEEM²,

Anam³

et al. 2023

IJCDS

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Internet corporations and other types of enterprises are quickly implementing NoSQL technology rather than merely SQL because of the introduction of Big Data. The simplicity of the design, the capacity to scale horizontally, and tighter control over availability are some benefits. Because of the schema-free data model they use, more businesses are beginning to recognize that NoSQL databases are a superior method for managing bulk amount of structured, semi-structured, and unstructured data currently being collected and handled. As a result, NoSQL database is increasingly viewed as a viable alternative to relational databases. For instance, NoSQL database is regularly utilized to gather and store data about social networking sites. This article targets to introduce the ideas that underpin NoSQL, as well as a review of the pertinent literature, an overview of the many types of NoSQL databases, and reasons both for and against the use of NoSQL. To analyze the known advantages of NoSQL and demonstrate the distinctions between the SQL and NoSQL methods, a simple SWOT analysis was performed. In the final part of the article, we draw some comparative studies of the NoSQL database and conclusions to broaden the scope of our previous work.

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SQL Versus NoSQL Databases to Assess Their Appropriateness for Big Data Application

Cited by 9 publications

References 0 publications

Analysis of E-Commerce Purchase Patterns Using Big Data: An Integrative Approach to Understanding Consumer Behavior

Analysis of E-Commerce Purchase Patterns Using Big Data: An Integrative Approach to Understanding Consumer Behavior

Cloud based evaluation of databases for stock market data

A State of Art Survey for Big Data Processing and NoSQL Database Architecture

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