Application of Keyword Dynamic Query Software in Relational Database based on Big Data

2020 ◽  
Author(s):  
Yandong Yu ◽  
Yuge Yao
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Dynamic Query

scholarly journals Volume-Adaptive Big Data Model for Relational Databases

2021 ◽  
Vol 10 (3) ◽  
pp. 2283-2295
Keyword(s):  
Big Data ◽  
Distributed Systems ◽  
Relational Database ◽  
Database Management ◽  
Relational Databases ◽  
Data Partitioning ◽  
Database Management System ◽  
Np Hard ◽  
Related Data ◽  
Partitioning Strategy

Big data is traditionally associated with distributed systems and this is understandable given that the volume dimension of Big Data appears to be best accommodated by the continuous addition of resources over a distributed network rather than the continuous upgrade of a central storage resource. Based on this implementation context, non- distributed relational database models are considered volume-inefficient and a departure from their usage contemplated by the database community. Distributed systems depend on data partitioning to determine chunks of related data and where in storage they can be accommodated. In existing Database Management Systems (DBMS), data partitioning is automated which in the opinion of this paper does not give the best results since partitioning is an NP-hard problem in terms of algorithmic time complexity. The NP-hardness is shown to be reduced by a partitioning strategy that relies on the discretion of the programmer which is more effective and flexible though requires extra coding effort. NP-hard problems are solved more effectively by a combination of discretion rather than full automation. In this paper, the partitioning process is reviewed and a programmer-based partitioning strategy implemented for an application with a relational DBMS backend. By doing this, the relational DBMS is made adaptive in the volume dimension of big data. The ACID properties (atomicity, consistency, isolation, and durability) of the relational database model which constitutes a major attraction especially for applications that process transactions is thus harnessed. On a more general note, the results of this research suggest that databases can be made adaptive in the areas of their weaknesses as a one-size-fits- all database management system may no longer be feasible.

Security of NoSQL Database Against Intruders

2019 ◽  
Vol 13 (1) ◽  
pp. 5-12 ◽  
Author(s):  
Khaleel Ahmad ◽  
Mohammad Shoaib Alam ◽  
Nur Izura Udzir
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Large Scale ◽  
Distributed Databases ◽  
Structural Data ◽  
Database Management System ◽  
Base System ◽  
Security Measures ◽  
Nosql Databases ◽  
Nosql Database

Background: The evolution of distributed web-based applications and cloud computing has brought about the demand to store a large amount of big data in distributed databases. Such efficient systems offer excessive availability and scalability to users. The new type of database resolves many new challenges especially in large-scale and high concurrency applications which are not present in the relational database. NoSQL refers to non-relational databases that are different from the Relational Database Management System. Objective: NoSQL has many features over traditional databases such as high scalability, distributed computing, lower cost, schema flexibility, semi or un-semi structural data and no complex relationship. Method: NoSQL databases are “BASE” Systems. The BASE (Basically Available, Soft state, Eventual consistency), formulates the CAP theorem the properties of which are used by BASE System. The distributed computer system cannot guarantee all of the following three properties at the same time that is consistency, availability and partition tolerance. Results: As progressively sharp big data is saved in NoSQL databases, it is essential to preserve higher security measures to ensure safe and trusted communication across the network. In this patent, we describe the security of NoSQL database against intruders which is growing rapidly. Conclusion: This patent also defines probably the most prominent NoSQL databases and describes their security aspects and problems.

Use of Big Data in Aviation

2019 ◽  
pp. 436-452
Author(s):  
Roman Odarchenko ◽  
Zohaib Hassan ◽  
Abnash Zaman
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Management System ◽  
Database Management System ◽  
Relational Models ◽  
Nosql Databases ◽  
Major Shift ◽  
Logical Modeling ◽  
Common Problems ◽  
Relational Database Management

The expansion of data and its efficient handling is becoming a more popular tendency in recent times bringing new difficulties to learn new avenues. Data analytics can be done more proficiently with the availability of distributed architecture of not only SQL (NoSQL) databases. Technological advancements around us are changing very rapidly, and major shift is being carried out, a switch from relational to non-relational world. When moving from relational to non-relational models, database administrators face common problems due to the fact that NoSQL is a no-schema database. The purpose of conducting this research is to propose a mechanism by which the schema of a relational database management system and its data can be transformed into big data by following some standardize guidelines. This model can be quite useful for relational database administrators by enabling them to give attention to logical modeling rather than procedural writing for each and every SQL to NoSQL transition.

Which Way to Go for the Future

2018 ◽  
pp. 311-328
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Data Model ◽  
Driving Force ◽  
Relational Databases ◽  
High Availability ◽  
Nosql Databases ◽  
The Future ◽  
Data Requirements ◽  
Open Issues

The chapter presents how relational databases answer to typical NoSQL features, and, vice versa, how NoSQL databases answer to typical relational features. Open issues related to the integration of relational and NoSQL databases, as well as next database generation features are discussed. The big relational database vendors have continuously worked to incorporate NoSQL features into their databases, as well as NoSQL vendors are trying to make their products more like relational databases. The convergence of these two groups of databases has been a driving force in the evolution of database market, in establishing a new level of focus to resolving big data requirements, and in enabling users to fully use data potential, wherever data is stored, in relational or NoSQL databases. In turn, the database of choice in the future will likely be one that provides the best of both worlds: flexible data model, high availability, and enterprise reliability.

Integrating NoSQL, Relational Database, and the Hadoop Ecosystem in an Interdisciplinary Project involving Big Data and Credit Card Transactions

2017 ◽  
pp. 443-451 ◽  
Author(s):  
Romulo Alceu Rodrigues ◽  
Lineu Alves Lima Filho ◽  
Gildarcio Sousa Gonçalves ◽  
Lineu F. S. Mialaret ◽  
Adilson Marques da Cunha ◽  
...  
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Credit Card ◽  
Interdisciplinary Project ◽  
Hadoop Ecosystem

Relational Database Architecture Refine Based on the Storage Space Estimate

2014 ◽  
Vol 536-537 ◽  
pp. 647-652
Author(s):  
Li Yue
Keyword(s):  
Big Data ◽  
Relational Database ◽  
New Method ◽  
Storage Space ◽  
Important Thing ◽  
Database Architecture

This paper gives you a new method to dispose the coming big data. How to storage so much data in finite memorizer is an important thing we must be facing. We can refine the relational-database architecture by estimating the storage scale.

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