scholarly journals IMPLEMENTASI WEBSITE PENCARIAN KOS DENGAN NoSQL

2017 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Danny Kriestanto ◽  
Alif Benden Arnado
Keyword(s):  
Data Storage ◽  
Structure Data ◽  
Relational Databases ◽  
New Technology ◽  
Unstructured Data ◽  
Nosql Databases ◽  
Storage Technology ◽  
Nosql Database ◽  
Boarding House ◽  
New Type

The new technology of database has moved forward the relational databases. Now, the massive and unstructured data encourage experts to create a new type of database without using query. One of this technology is called NoSQL (Not Only SQL). One of the developing RDBMS that using this technique is MongoDB, which already supporting data storage technology that is no longer need for structured tables and rigid-typed of data. The schema was made flexible to handle the changes of data. The MongoDB data collecting characteristics in the form of arrays is considered suitable for the implementation of boarding house searching where each of the boarding houses have their own scenario structures. MongoDB also supports several programming language, including PHP with Bootstrap material as interface. The results of the research showed that there are alot of difference in implementing a NoSQL database with the regular relational one. NoSQL databases considered alot more complicated in structure, data type, even the CRUD system. The results also showed that in order to view an array inside another array will need two processes.

scholarly journals Access Control Models in NoSQL Databases: An Overview

2019 ◽  
Vol 8 (1) ◽  
pp. 1-9
Author(s):  
Ashwaq A. Alotaibi, Reem M. Alotaibi and Nermin Hamza Ashwaq A. Alotaibi, Reem M. Alotaibi and Nermin Hamza
Keyword(s):  
Access Control ◽  
Relational Databases ◽  
Unstructured Data ◽  
Huge Amount ◽  
Sensitive Data ◽  
Nosql Databases ◽  
Security Issues ◽  
Access Control Models ◽  
Control Models ◽  
Nosql Database

Recently non-relational databases known as NoSQL have become most popular for handling a huge amount of data. Many organizations move from relational databases towards NoSQL databases due to the growing popularity of cloud computing and big data. NoSQL database is designed to handle unstructured data like documents, e-mails, and social media efficiently. It uses distributed and cooperating devices to store and retrieve data. As a large number of people storing sensitive data in NoSQL databases, security issues become critical concerns. NoSQL has many advantages like scalability and availability, but it suffers from some security issues like weak authorization mechanisms. This paper reviews the different models of NoSQL databases and the security issues concerning these databases. In addition, we present the existing access control models in different NoSQL databases.

scholarly journals Performance Benchmarking of Key-Value Store NoSQL Databases

2018 ◽  
Vol 8 (6) ◽  
pp. 5333
Author(s):  
Omoruyi Osemwegie ◽  
Kennedy Okokpujie ◽  
Nsikan Nkordeh ◽  
Charles Ndujiuba ◽  
Samuel John ◽  
...  
Keyword(s):  
Data Storage ◽  
Web Applications ◽  
Query Language ◽  
Research Work ◽  
Database Systems ◽  
Nosql Databases ◽  
Performance Benchmarking ◽  
Nosql Database ◽  
Structured Query Language ◽  
Web Developers

<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.</p>

Storage Infrastructure for Big Data and Cloud

2014 ◽  
pp. 110-128 ◽  
Author(s):  
Anupama C. Raman
Keyword(s):  
Big Data ◽  
Real Time ◽  
Data Storage ◽  
Unstructured Data ◽  
Storage Area Networks ◽  
Storage Technology ◽  
Object Based ◽  
Storage Area ◽  
Storage Technologies ◽  
Big Data Storage

Unstructured data is growing exponentially. Present day storage infrastructures like Storage Area Networks and Network Attached Storage are not very suitable for storing huge volumes of unstructured data. This has led to the development of new types of storage technologies like object-based storage. Huge amounts of both structured and unstructured data that needs to be made available in real time for analytical insights is referred to as Big Data. On account of the distinct nature of big data, the storage infrastructures for storing big data should possess some specific features. In this chapter, the authors examine the various storage technology options that are available nowadays and their suitability for storing big data. This chapter also provides a bird's eye view of cloud storage technology, which is used widely for big data storage.

Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases

2016 ◽  
pp. 133-162 ◽  
Author(s):  
Berkay Aydin ◽  
Vijay Akkineni ◽  
Rafal A Angryk
Keyword(s):  
Data Storage ◽  
Relational Databases ◽  
Large Scale ◽  
Database Systems ◽  
Distributed Database ◽  
Data Models ◽  
Trajectory Data ◽  
Nosql Databases ◽  
Distributed Database Systems ◽  
Partitioned Data

With the ever-growing nature of spatiotemporal data, it is inevitable to use non-relational and distributed database systems for storing massive spatiotemporal datasets. In this chapter, the important aspects of non-relational (NoSQL) databases for storing large-scale spatiotemporal trajectory data are investigated. Mainly, two data storage schemata are proposed for storing trajectories, which are called traditional and partitioned data models. Additionally spatiotemporal and non-spatiotemporal indexing structures are designed for efficiently retrieving data under different usage scenarios. The results of the experiments exhibit the advantages of utilizing data models and indexing structures for various query types.

scholarly journals PERBANDINGAN PERFORMANSI DATABASE MONGODB DAN MYSQL DALAM APLIKASI FILE MULTIMEDIA BERBASIS WEB

2018 ◽  
Vol 6 (1) ◽  
pp. 63
Author(s):  
Mesri Silalahi
Keyword(s):  
Data Storage ◽  
Information Needs ◽  
Relational Databases ◽  
Performance Comparison ◽  
Web Based ◽  
File Storage ◽  
Nosql Database ◽  
Computer Resources ◽  
Important Building Block ◽  
Multimedia File

Database appeared and began to develop in line with the needs of processing and data storage to meet the information needs. Database is part of an important building block in an information system. In addition to a relational database (SQL), which stores structured datas in tables with defined schemes, there is a non-relational databases (NoSQL) with a dynamic scheme or unstructured. This study will compare the performance between NoSQL database (MongoDB) and SQL database (MySQL) for a web-based multimedia file storage application that stores files as BLOBs. Performance comparison is based on the speed of execution and the computer resources usage (CPU, memory, and virtual memory).

NoSQL Databases

2015 ◽  
pp. 109-152 ◽  
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.

scholarly journals Contemporary Trends in the Development of Databases

2021 ◽  
Vol 27 (1) ◽  
pp. 5-15
Keyword(s):  
Relational Databases ◽  
Point Of View ◽  
Nosql Databases ◽  
Advantages And Disadvantages ◽  
Different Types ◽  
Long Time ◽  
Structured Information ◽  
New Type ◽  
Operational Activities ◽  
Almost All

Databases have been established for a long time as an efficient and reliable technology for organizing and storing data in almost all areas of human activity. In addition to their widespread use in the operational activities of practically all enterprises and organizations, they are also sources of data for research and analysis of economic processes. Databases were developed rapidly in the second half of the 20th century and as a result relational databases emerged, which are an extremely powerful tool for storing and accessing data. Since the beginning of the 21st century, with the extraordinary increase in the volume of stored and processed information, as well as the significant part of unstructured and semi-structured information, a new type of databases, named NoSQL databases, have emerged and developed. The article attempts to define the characteristics of different types of databases, analyzing their advantages and disadvantages and outlining their areas of application on this basis. The trends in the development of the databases from the point of view of the author are also presented.

scholarly journals Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zain Aftab ◽  
Waheed Iqbal ◽  
Khaled Mohamad Almustafa ◽  
Faisal Bukhari ◽  
Muhammad Abdullah
Keyword(s):  
Relational Database ◽  
Business Intelligence ◽  
Relational Databases ◽  
State Of The Art ◽  
Schema Mapping ◽  
Excellent Performance ◽  
Nosql Databases ◽  
Nosql Database ◽  
Domain Expertise ◽  
Database Transformation

Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL database into a structured database. In this paper, we proposed and evaluated an efficient method to transform a NoSQL database into a relational database automatically. In our experimental evaluation, we used MongoDB as a NoSQL database, and MySQL and PostgreSQL as relational databases to perform transformation tasks for different dataset sizes. We observed excellent performance, compared to the existing state-of-the-art methods, in transforming data from a NoSQL database into a relational database.

scholarly journals Comparative study of NoSQL databases for big data storage

2018 ◽  
Vol 7 (2.6) ◽  
pp. 83
Author(s):  
Gourav Bathla ◽  
Rinkle Rani ◽  
Himanshu Aggarwal
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Relational Databases ◽  
Large Scale ◽  
Technology Selection ◽  
Business Organizations ◽  
Nosql Databases ◽  
Real Solutions ◽  
Adequate Knowledge ◽  
Long Time

Big data is a collection of large scale of structured, semi-structured and unstructured data. It is generated due to Social networks, Business organizations, interaction and views of social connected users. It is used for important decision making in business and research organizations. Storage which is efficient to process this large scale of data to extract important information in less response time is the need of current competitive time. Relational databases which have ruled the storage technology for such a long time seems not suitable for mixed types of data. Data can not be represented just in the form of rows and columns in tables. NoSQL (Not only SQL) is complementary to SQL technology which can provide various formats for storage that can be easily compatible with high velocity,large volume and different variety of data. NoSQL databases are categorized in four techniques- Column oriented, Key Value based, Graph based and Document oriented databases. There are approximately 120 real solutions existing for these categories; most commonly used solutions are elaborated in Introduction section. Several research works have been carried out to analyze these NoSQL technology solutions. These studies have not mentioned the situations in which a particular data storage technique is to be chosen. In this study and analysis, we have tried our best to provide answer on technology selection based on specific requirement to the reader. In previous research, comparisons amongNoSQL data storage techniques have been described by using real examples like MongoDB, Neo4J etc. Our observation is that if users have adequate knowledge of NoSQL categories and their comparison, then it is easy for them to choose best suitable category and then real solutions can be selected from this category.

scholarly journals Application of Heterogeneous Network Oriented to NoSQL Database in Optimal Postevaluation Indexes of Construction Projects

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Airong Yang ◽  
Guoxin Yu
Keyword(s):  
Performance Evaluation ◽  
Data Storage ◽  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Relational Databases ◽  
Corporate Performance ◽  
High Growth ◽  
Third Party ◽  
Project Leader ◽  
Nosql Database

With the advent of the Internet Web 2.0 era, storage devices used to store website data are developing at an ever-increasing high-growth rate and a diversified trend. The focus on the structured data storage model has reduced the responsiveness of traditional relational databases to data changes. NoSQL database is scalable, has a powerful and flexible data model and a large amount of data, and has an increasing application potential in the memory field. Heterogeneous networks are composed of third-party computers, network equipment, and systems. Network types are usually used for other protocols to support other functions and applications. The research on heterogeneous networks can be traced back to the BARWAN project that started in 1995 at the University of California, Berkeley. The project leader RHKatz merged multiple types of nested networks for the first time to form heterogeneous network requirements for various future terminal services. Construction engineering refers to an engineering entity formed by installing pipelines and equipment that support the construction of various houses and ancillary facilities. “House construction” refers to projects with roofs, beams, columns, walls, and foundations that can form internal spaces to meet people’s needs in production, living, learning, and public activities. Among them, the engineering evaluation index is a statistical index used to evaluate and compare the quality and effects of social and economic activities through the use of equipment, such as capital turnover rate and employee labor efficiency. It is the exchange of corporate performance evaluation content and the expression of corporate performance evaluation content.

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