A Comparative Study of NoSQL Databases

Bagga, Simmi; Sharma, Añil

doi:10.1007/978-981-15-8297-4_5

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…This led to BASE systems. These lack traditional transactions and add data model limitations to improve partitioning [38].…”

Section: Characteristics Of Nosql Databasesmentioning

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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“…This led to BASE systems. These lack traditional transactions and add data model limitations to improve partitioning [38].…”

Section: Characteristics Of Nosql Databasesmentioning

confidence: 99%

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

ALI¹,

NAEEM²,

Anam³

et al. 2023

IJCDS

View full text Add to dashboard Cite

show abstract

“…From an operational complexity view normalized forms [29] and user rights assignment [24] play a central role. Document databases typically operate on structured documents, usually in extensible markup language (XML) or JavaScript object notation (JSON) format [4]. The prospect of developing normalization and embedding operations in MongoDB is explored in [20], while the expressivity of MongoDB queries is the subject of [8].…”

Section: Previous Workmentioning

confidence: 99%

Recommending Database Architectures for Social Queries: A Twitter Case Study

Marountas

Drakopoulos

Mylonas

et al. 2021

IFIP Advances in Information and Communication Technology

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Database deployment is a complex task depending on a multitude of operational parameters such as anticipated data scaling trends, expected type and volume of queries, uptime requirements, replication policies, available budget, and personnel training and experience. Thus, enterprise database administrators eventually rely on various performance metrics in conjunction to existing company policies in order to determine the best possible solution under these constraints. The recent advent of NoSQL databases, including graph databases such as Neo4j and document stores like MongoDB, added another degree of freedom in database selection since for a number of years relational databases such as PostgreSQL were the only available technology. In this work the scaling characteristics of a representative set of social queries executed on virtual machine installations of PostgreSQL and MongoDB are evaluated on a large volume of political tweets regarding Brexit. Moreover, Wiener filters for predicting the execution time of social query windows of fixed length over both databases are designed.

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“…The MongoDB database has been created in C++ by the 10gen firm since 2007, when it was working on a broadly distributed data cloud computing system akin to Google's App Engine. The initial version was released in 2009, but version 1.4 was only declared commercially acceptable in 2010 (7) .…”

Section: Introductionmentioning

confidence: 99%

A Study of Performance and Comparison of NoSQL Databases: MongoDB, Cassandra, and Redis Using YCSB

Kausar¹,

Nasar²,

Soosaimanickam³

2022

IJST

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Background/Objectives: Relational databases are a commonly utilized technology that allows for the storage, administration, and retrieval of various data schemas. However, for certain big databases, executing queries can become a time-consuming and inefficient procedure. Furthermore, storing enormous volumes of data necessitates servers with greater capacity and scalability. Relational databases have limits when it comes to dealing with scalability for big amounts of data. On the other hand, non-relational database systems, often known as NoSQL, were created to better fulfill the demands of key-value storing of enormous volumes of records. However, there are several NoSQL options, and the majority have not yet been extensively compared. The goal of this research is to examine different NoSQL databases and evaluate their performance in terms of typical data storage and retrieval. Methods: In this study, we use the YCSB tool to measure the performance of three NoSQL databases: MongoDB, Cassandra, and Redis. We test six different workloads with 100000, 250000, 500000, 750000, and 1000000 operations. Our test was designed with five different operations, i.e., 100000, 250000, 500000, 750000, and 1000000, with six different workloads to see which database is most suitable for applications which use a large amount of data to process. Findings: MongoDB is a superior performing NoSQL database among Cassandra and Redis. The numerous optimizations used by the designers of NoSQL solutions to improve performance, such as good cache memory operation, have a direct impact on the execution time. In all workloads except workload D, MongoDB has significantly reduced latency across all operation counts. Novelty: We also measure the average latency of different workload scenarios that include a mix of read, write, and update activities.

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A Comparative Study of NoSQL Databases

Cited by 4 publications

References 9 publications

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

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

Recommending Database Architectures for Social Queries: A Twitter Case Study

A Study of Performance and Comparison of NoSQL Databases: MongoDB, Cassandra, and Redis Using YCSB

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