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>

Bind but Dynamic Technique

2009 ◽  
pp. 880-890
Author(s):  
Ahmad Hammoud ◽  
Ramzi A. Haraty
Keyword(s):  
Web Application ◽  
Efficient Solution ◽  
Web Applications ◽  
Query Language ◽  
Sql Injection ◽  
Injection Attacks ◽  
Dynamic Technique ◽  
Structured Query Language ◽  
Sql Injection Attacks ◽  
Web Developers

Most Web developers underestimate the risk and the level of damage that might be caused when Web applications are vulnerable to SQL (structured query language) injections. Unfortunately, Web applications with such vulnerability constitute a large part of today’s Web application landscape. This article aims at highlighting the risk of SQL injection attacks and provides an efficient solution.

scholarly journals Research of NOSQL and SQL and Designing a Better Database Schema for Databases

2019 ◽  
Vol 8 (6S) ◽  
pp. 177-182
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Query Language ◽  
Storage System ◽  
Database Schema ◽  
Nosql Databases ◽  
Storage Security ◽  
File Storage ◽  
Structured Query Language ◽  
Day By Day

The amount of data storage and querying is increasing day by day. The requirement of data-storage, security, scalability and management is an alarming issue. Structured Query Language (SQL) databases was designed to overcome most of the trouble faced over tradition file storage system. But the alarming rate of data storage leads to Not only Structured Query Language (NoSQL) databases. in this paper, various aspects of SQL and NoSQL are compared with respect to their data management and to develop a better schema for data management is attempted

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 Analysis of the possibilities of optimizing SQL queries

2021 ◽  
Vol 19 ◽  
pp. 151-158
Author(s):  
Piotr Rymarski ◽  
Grzegorz Kozieł
Keyword(s):  
Relational Database ◽  
Web Applications ◽  
Query Language ◽  
Database Systems ◽  
Sql Server ◽  
Management Systems ◽  
Relational Database Systems ◽  
The Impact ◽  
Relational Database Management ◽  
Test Scenarios

Most of today's web applications run on relational database systems. Communication with them is possible through statements written in Structured Query Language (SQL). This paper presents the most popular relational database management systems and describes common ways to optimize SQL queries. Using the research environment based on fragment of the imdb.com database, implementing OracleDb, MySQL, Microsoft SQL Server and PostgreSQL engines, a number of test scenarios were performed. The aim was to check the performance changes of SQL queries resulting from syntax modication while maintaining the result, the impact of database organization, indexing and advanced mechanisms aimed at increasing the eciency of operations performed, delivered in the systems used. The tests were carried out using a proprietary application written in Java using the Hibernate framework.

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.

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 Hindi Language Interface to Database

2020 ◽  
Vol 32 ◽  
pp. 01007
Author(s):  
Rachana Dubey ◽  
Tejal Kawale ◽  
Twisha Choudhary ◽  
Vaibhav Narawade
Keyword(s):  
Natural Language ◽  
Data Storage ◽  
Query Language ◽  
Database Systems ◽  
Sources Of Information ◽  
Common People ◽  
Storage And Retrieval ◽  
Natural Language Query ◽  
Sql Query ◽  
Information Database

In our everyday lives we require information to accomplish daily tasks. Database is one of the most important sources of information. Database systems have been widely used in data storage and retrieval. However, to extract information from databases, we need to have some knowledge of database languages like SQL. But SQL has predefined structures and format, so it is hard for the non-expert users to formulate the desired query. To override this complexity, we have turned to natural language to retrieve information from database, which can be an ideal channel between a non-technical user and the application. But the application cannot understand natural language so an interface is required. This interface is capable of converting the user’s natural language query to an equivalent database language query. In this paper, we address the system architecture for translating a Hindi sentence in the form of an audio to an equivalent SQL query. The users don’t need to learn any formal query language; hence it’s easy to use for common people.

scholarly journals Hybrid Mobile-App. on Multi-MEC Platforms in NFV Environment

2018 ◽  
Vol 7 (4.38) ◽  
pp. 383
Author(s):  
Jinsul Kim ◽  
Akm Ashiquzzaman ◽  
Van Quan Nguyen ◽  
Sang Woo Kim
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Large Scale ◽  
Web Applications ◽  
Rapid Development ◽  
Query Languages ◽  
Vital Role ◽  
Mobile App ◽  
Network Function Virtualization ◽  
Nosql Databases

In recent times, practicality of web applications has become more reliant upon big-data orientated materials such 4K videos, hi-def. resolution images, lossless audios and massive texts. Structured Query Languages (SQL) faces compatibility issues with large scale databases. Because of this data storage problem, NoSQL databases are used for storing big-data. NoSQL databases have been recently gaining traction with many options such MongoDB, CouchDB, Redis and Apache Cassandra. One of the major restrictions companies, enterprises and developers encounter during developing an application is multiplicative cost of building a native programing across different platforms. Besides, network Function Virtualization (NFV) plays a vital role for providing services for utilizing such applications in larger and more effective scale. Hence, in this paper, we discussed our main motivation behind selecting Iconic Framework, a hybrid system for rapid development real-time application based on Firebase in the NFV environment cooperating with Mobile Edge Computing (MEC). As a result, this approach provides comparatively flexible features.  

scholarly journals Benchmarking geospatial database on Kubernetes cluster

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Bharti Sharma ◽  
Poonam Bansal ◽  
Mohak Chugh ◽  
Adisakshya Chauhan ◽  
Prateek Anand ◽  
...  
Keyword(s):  
Spatial Data ◽  
Query Language ◽  
Research Work ◽  
Nosql Databases ◽  
Geospatial Database ◽  
Computationally Expensive ◽  
Execution Times ◽  
Container Orchestration ◽  
Geospatial Databases ◽  
Geo Database

AbstractKubernetes is an open-source container orchestration system for automating container application operations and has been considered to deploy various kinds of container workloads. Traditional geo-databases face frequent scalability issues while dealing with dense and complex spatial data. Despite plenty of research work in the comparison of relational and NoSQL databases in handling geospatial data, there is a shortage of existing knowledge about the performance of geo-database in a clustered environment like Kubernetes. This paper presents benchmarking of PostgreSQL/PostGIS geospatial databases operating on a clustered environment against non-clustered environments. The benchmarking process considers the average execution times of geospatial structured query language (SQL) queries on multiple hardware configurations to compare the environments based on handling computationally expensive queries involving SQL operations and PostGIS functions. The geospatial queries operate on data imported from OpenStreetMap into PostgreSQL/PostGIS. The clustered environment powered by Kubernetes demonstrated promising improvements in the average execution times of computationally expensive geospatial SQL queries on all considered hardware configurations compared to their average execution times in non-clustered environments.

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