A Novel Solution of Distributed Memory NoSQL Database for Cloud Computing

Cloud Computing is a new computing model that distributes the computation on a resource pool. The need for a scalable database capable of expanding to accommodate growth has increased with the growing data in web world. More familiar Cloud Computing vendors such as Amazon Web Services, Microsoft, Google, IBM and Rackspace offer cloud based Hadoop and NoSQL database platforms to process Big Data applications. Variety of services are available that run on top of cloud platforms freeing users from the need to deploy their own systems. Nowadays, integrating Big Data and various cloud deployment models is major concern for Internet companies especially software and data services vendors that are just getting started themselves. This chapter proposes an efficient architecture for integration with comprehensive capabilities including real time and bulk data movement, bi-directional replication, metadata management, high performance transformation, data services and data quality for customer and product domains.

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NoSQL Databases

Handbook of Research on Securing Cloud-Based Databases with Biometric Applications - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-4666-6559-0.ch006 ◽

2015 ◽

pp. 109-152 ◽

Cited By ~ 2

Author(s):

Mainak Adhikari ◽

Sukhendu Kar

Keyword(s):

Cloud Computing ◽

Social Networking ◽

Data Storage ◽

Social Networking Sites ◽

Nosql Databases ◽

Data Intensive ◽

Huge Data ◽

Nosql Database ◽

Real Time Applications ◽

Data Intensive Applications

NoSQL database provides a mechanism for storage and access of data across multiple storage clusters. NoSQL dabases are finding significant and growing industry to meet the huge data storage requirements of Big data, real time applications, and Cloud Computing. NoSQL databases have lots of advantages over the conventional RDBMS features. NoSQL systems are also referred to as “Not only SQL” to emphasize that they may in fact allow Structured language like SQL, and additionally, they allow Semi Structured as well as Unstructured language. A variety of NoSQL databases having different features to deal with exponentially growing data intensive applications are available with open source and proprietary option mostly prompted and used by social networking sites. This chapter discusses some features and challenges of NoSQL databases and some of the popular NoSQL databases with their features on the light of CAP theorem.

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Architecture for Big Data Storage in Different Cloud Deployment Models

Advances in Data Mining and Database Management - Handbook of Research on Big Data Storage and Visualization Techniques ◽

10.4018/978-1-5225-3142-5.ch008 ◽

2018 ◽

pp. 196-226 ◽

Cited By ~ 2

Author(s):

Chandu Thota ◽

Gunasekaran Manogaran ◽

Daphne Lopez ◽

Revathi Sundarasekar

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Storage ◽

High Performance ◽

Data Services ◽

Big Data Applications ◽

Nosql Database ◽

Amazon Web Services ◽

Product Domains ◽

Scalable Database

Cloud Computing is a new computing model that distributes the computation on a resource pool. The need for a scalable database capable of expanding to accommodate growth has increased with the growing data in web world. More familiar Cloud Computing vendors such as Amazon Web Services, Microsoft, Google, IBM and Rackspace offer cloud based Hadoop and NoSQL database platforms to process Big Data applications. Variety of services are available that run on top of cloud platforms freeing users from the need to deploy their own systems. Nowadays, integrating Big Data and various cloud deployment models is major concern for Internet companies especially software and data services vendors that are just getting started themselves. This chapter proposes an efficient architecture for integration with comprehensive capabilities including real time and bulk data movement, bi-directional replication, metadata management, high performance transformation, data services and data quality for customer and product domains.

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An Empirical Study of NoSQL Databases for Big Data

Effective Big Data Management and Opportunities for Implementation - Advances in Data Mining and Database Management ◽

10.4018/978-1-5225-0182-4.ch004 ◽

2016 ◽

pp. 60-76

Author(s):

Wen-Chen Hu ◽

Naima Kaabouch ◽

Hongyu Guo ◽

Hung-Jen Yang

Keyword(s):

Cloud Computing ◽

Big Data ◽

Empirical Study ◽

Theoretical Approach ◽

Relational Databases ◽

High Volume ◽

Inventory Systems ◽

Nosql Databases ◽

Nosql Database ◽

The One

Relational databases have dominated the database markets for decades because they perform extremely well for traditional applications like electronic commerce and inventory systems. However, the relational databases do not suit some of the contemporary applications such as big data and cloud computing well because of various reasons like their low scalability and unable to handle a high volume of data. NoSQL (not only SQL) databases are part of the solution for developing those newer applications. The approach they use is different from the one used by relational databases. This chapter discusses NoSQL databases by using an empirical instead of theoretical approach. Other than introducing the types and features of generic NoSQL databases, practical NoSQL database programming and usage are shown by using MongoDB, a NoSQL database. A summary of this research is given at the end of this chapter.

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Deployment and Analysis of a Hybrid Shared/Distributed-Memory Parallel Visualization Tool for 3-D Oil Reservoir Grid on OpenStack Cloud Computing

IEEE Access ◽

10.1109/access.2020.3037731 ◽

2020 ◽

Vol 8 ◽

pp. 212280-212297

Author(s):

Ali A. El-Moursy ◽

Fadi N. Sibai ◽

Hanan Khaled ◽

Salwa M. Nassar ◽

Mohamed Taher

Keyword(s):

Cloud Computing ◽

Distributed Memory ◽

Oil Reservoir ◽

Visualization Tool ◽

Parallel Visualization

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Optimizing access to distributed memory pages in cloud computing systems based on shared everything architecture by using the method of discharge queue

Problems of Informatization and Management ◽

10.18372/2073-4751.4.10330 ◽

2015 ◽

Vol 4 (52) ◽

Author(s):

Е. И. Гусев

Keyword(s):

Cloud Computing ◽

Distributed Memory ◽

Computing Systems

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Bioinformatics Workflows With NoSQL Database in Cloud Computing

Evolutionary Bioinformatics ◽

10.1177/1176934319889974 ◽

2019 ◽

Vol 15 ◽

pp. 117693431988997

Author(s):

Polyane Wercelens ◽

Waldeyr da Silva ◽

Fernanda Hondo ◽

Klayton Castro ◽

Maria Emília Walter ◽

...

Keyword(s):

Cloud Computing ◽

Molecular Biology ◽

Database Systems ◽

Data Provenance ◽

Cloud Computing Environment ◽

Computational Environment ◽

Provenance Data ◽

Nosql Database ◽

Technical Details ◽

Bioinformatics Workflows

Scientific workflows can be understood as arrangements of managed activities executed by different processing entities. It is a regular Bioinformatics approach applying workflows to solve problems in Molecular Biology, notably those related to sequence analyses. Due to the nature of the raw data and the in silico environment of Molecular Biology experiments, apart from the research subject, 2 practical and closely related problems have been studied: reproducibility and computational environment. When aiming to enhance the reproducibility of Bioinformatics experiments, various aspects should be considered. The reproducibility requirements comprise the data provenance, which enables the acquisition of knowledge about the trajectory of data over a defined workflow, the settings of the programs, and the entire computational environment. Cloud computing is a booming alternative that can provide this computational environment, hiding technical details, and delivering a more affordable, accessible, and configurable on-demand environment for researchers. Considering this specific scenario, we proposed a solution to improve the reproducibility of Bioinformatics workflows in a cloud computing environment using both Infrastructure as a Service (IaaS) and Not only SQL (NoSQL) database systems. To meet the goal, we have built 3 typical Bioinformatics workflows and ran them on 1 private and 2 public clouds, using different types of NoSQL database systems to persist the provenance data according to the Provenance Data Model (PROV-DM). We present here the results and a guide for the deployment of a cloud environment for Bioinformatics exploring the characteristics of various NoSQL database systems to persist provenance data.

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Towards Scalability for Federated Identity Systems for Cloud-Based Environments

CLEI electronic journal ◽

10.19153/cleiej.18.3.2 ◽

2015 ◽

Author(s):

André Albino Pereira ◽

João Bosco M. Sobral ◽

Carla M. Westphall

Keyword(s):

Cloud Computing ◽

Distributed Memory ◽

Identity Management ◽

Management Systems ◽

Maximum Efficiency ◽

Authentication Protocols ◽

Identity Management Systems ◽

Federated Identity Management ◽

Federated Identity ◽

Computational Resources

As multi-tenant authorization and federated identity management systems for cloud computing matures, the provisioning of services using this paradigm allows maximum efficiency on business that requires access control. However, regarding scalability support, mainly horizontal, some characteristics of those approaches based on central authentication protocols are problematic. The objective of this work is to address these issues by providing an adapted sticky-session mechanism for a Shibboleth architecture using JASIG CAS. This alternative, compared with the recommended distributed memory approach, shown improved efficiency and less overall infrastructure complexity, as well as demanding less 58% of computational resources and improving throughput (requests per second) by 11%.

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Comparative Study Between the MySQL Relational Database and the MongoDB NoSQL Database

International Journal of Software Science and Computational Intelligence ◽

10.4018/ijssci.2021070104 ◽

2021 ◽

Vol 13 (3) ◽

pp. 38-63

Author(s):

Houcine Matallah ◽

Ghalem Belalem ◽

Karim Bouamrane

Keyword(s):

Social Networks ◽

Cloud Computing ◽

Comparative Study ◽

Electronic Commerce ◽

Relational Database ◽

Relational Databases ◽

Database Management System ◽

Nosql Databases ◽

Nosql Database ◽

Change Of Scale

NoSQL databases are new architectures developed to remedy the various weaknesses that have affected relational databases in highly distributed systems such as cloud computing, social networks, electronic commerce. Several companies loyal to traditional relational SQL databases for several decades seek to switch to the new “NoSQL” databases to meet the new requirements related to the change of scale in data volumetry, the load increases, the diversity of types of data handled, and geographic distribution. This paper develops a comparative study in which the authors will evaluate the performance of two databases very widespread in the field: MySQL as a relational database and MongoDB as a NoSQL database. To accomplish this confrontation, this research uses the Yahoo! Cloud Serving Benchmark (YCSB). This contribution is to provide some answers to choose the appropriate database management system for the type of data used and the type of processing performed on that data.

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