scholarly journals Consistency Models of NoSQL Databases

2019 ◽  
Vol 11 (2) ◽  
pp. 43 ◽  
Author(s):  
Miguel Diogo ◽  
Bruno Cabral ◽  
Jorge Bernardino
Keyword(s):  
Strong Consistency ◽  
Relational Databases ◽  
Daily Basis ◽  
Data Traffic ◽  
Nosql Databases ◽  
Network Partition ◽  
High Data ◽  
Consistency Model ◽  
Eventual Consistency ◽  
Consistency Models

Internet has become so widespread that most popular websites are accessed by hundreds of millions of people on a daily basis. Monolithic architectures, which were frequently used in the past, were mostly composed of traditional relational database management systems, but quickly have become incapable of sustaining high data traffic very common these days. Meanwhile, NoSQL databases have emerged to provide some missing properties in relational databases like the schema-less design, horizontal scaling, and eventual consistency. This paper analyzes and compares the consistency model implementation on five popular NoSQL databases: Redis, Cassandra, MongoDB, Neo4j, and OrientDB. All of which offer at least eventual consistency, and some have the option of supporting strong consistency. However, imposing strong consistency will result in less availability when subject to network partition events.

NOSQL DATABASES AS A DATA WAREHOUSE FOR DECISION SUPPORT SYSTEMS

2017 ◽  
Vol 185 (3) ◽  
pp. 124-131
Author(s):  
Jarosław KURPANIK
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Data Warehouse ◽  
Data Storage ◽  
Relational Databases ◽  
Support Systems ◽  
Large Data ◽  
Daily Basis ◽  
Nosql Databases ◽  
Big Data Storage

Nowadays, to some extent decision support systems are forced to base their operation on large data warehouses whose analysis is difficult and time consuming. This is why where data are stored becomes vital. The use of an efficient and productive data warehouse for this purpose can significantly improve application/system operation. Currently one of the most common solutions used in Big Data storage and quick processing are non-relational databases NoSQL. They are a relatively new solution, however, their development is dy-namic and their market share is increased on a daily basis, which means that it worth in-vestigating what they offer.

Formalizing the Mapping of UML Conceptual Schemas to Column-Oriented Databases

2018 ◽  
Vol 14 (3) ◽  
pp. 44-68 ◽  
Author(s):  
Fatma Abdelhedi ◽  
Amal Ait Brahim ◽  
Gilles Zurfluh
Keyword(s):  
Big Data ◽  
Data Warehouse ◽  
Relational Databases ◽  
Traditional Approach ◽  
Physical Models ◽  
Decision Making Process ◽  
Nosql Databases ◽  
Care Field ◽  
Sufficient Degree

Nowadays, most organizations need to improve their decision-making process using Big Data. To achieve this, they have to store Big Data, perform an analysis, and transform the results into useful and valuable information. To perform this, it's necessary to deal with new challenges in designing and creating data warehouse. Traditionally, creating a data warehouse followed well-governed process based on relational databases. The influence of Big Data challenged this traditional approach primarily due to the changing nature of data. As a result, using NoSQL databases has become a necessity to handle Big Data challenges. In this article, the authors show how to create a data warehouse on NoSQL systems. They propose the Object2NoSQL process that generates column-oriented physical models starting from a UML conceptual model. To ensure efficient automatic transformation, they propose a logical model that exhibits a sufficient degree of independence so as to enable its mapping to one or more column-oriented platforms. The authors provide experiments of their approach using a case study in the health care field.

scholarly journals Analysis And Performance Comparison of Microwave And WiFi 802.11ac Based Backhaul For Long Term Evolution Network In Urban Area

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Nida Nurvira ◽  
Anggun Fitrian Isnawati ◽  
Achmad Rizal Danisya
Keyword(s):  
Network Design ◽  
Performance Standards ◽  
Performance Comparison ◽  
Throughput Capacity ◽  
Data Traffic ◽  
Core Network ◽  
Lte Networks ◽  
Link Capacity ◽  
Average Value ◽  
High Data

Increasing user requirements for LTE networks, data traffic from eNodeB to core network is also increases, therefore, the recommended solution for meeting this high data traffic is to use a backhaul network design. Backhaul is the path or network used to connect eNodeB with the core network. In this research, backhaul technology used is wi-fi 802.11ac backhaul and microwave backhaul. In this study begins by collecting existing data, then perform capacity calculations to find out the number of eNodeB needed and to find out the capacity of the backhaul links to be designed, then determine the antenna height to achieve LOS conditions, then calculate the desired performance standards and calculate the backhaul network link budget on microwave and wi-fi technologies. Based on the calculation results in terms of capacity, the total user target is 90,167 users and has a throughput capacity per eNodeB of 61 Mbps. In the link-capacity calculation, the total link capacity is 427 Mbps. From the simulation results that using microwave technology, the average RSL value is -30.90 dBm, the value meets the -57 dBm threshold standard and the value of availability does not meet the standard of 99.999% because the average value obtained is 99.998095%. Whereas for wi-fi technology, the average RSL value is -39.24 dBm and meet the -72 dBm threshold standard, for the average availability value meets 99.999% standard, with a value of 100%. From the results of the two technologies, can be conclude that the wi-fi technology is more suitable for the use of backhaul network design in Ciputat Sub-district.

Handoff Management in Macro-Femto Cellular Networks

2019 ◽  
pp. 227-249
Author(s):  
Muhammad Faheem Mustafa ◽  
Ayaz Ahmad ◽  
Raheel Ahmed
Keyword(s):  
Cellular Networks ◽  
Base Station ◽  
Data Traffic ◽  
Core Network ◽  
Handoff Management ◽  
High Data ◽  
Cell Network ◽  
Network Operation ◽  
Comprehensive Survey ◽  
Time Required

With the rapid increase in data traffic and high data rate demands from cellular users, conventional cellular networks are becoming insufficient to fulfill these requirements. Femto cells are integrated in macro cellular network to increase the capacity, coverage, and to fulfill the increasing demands of the users. Time required for handoff process between the cells became more sensitive and complex with the introduction of femto cells in the network. Public internet which connect the femto base station with the mobile core network induces higher latency if conventional handoff procedures are also employed in macro-femto cell network. So, handoff process will become slower and network operation will become insufficient. Some standards, procedures, and protocols should be defined for macro-femto cell network rather than using existing protocols. This chapter presents a comprehensive survey of handoff process, types of handoff in macro-femto cell network, and proposed methods and schemes for frequent and unnecessary handoff reduction for efficient network operation.

How NoSQL Databases Work

2018 ◽  
pp. 124-175
Keyword(s):  
Distributed Storage ◽  
Practical Implementation ◽  
Query Execution ◽  
Nosql Databases ◽  
Consistency Model ◽  
Nosql Database ◽  
Distributed Cluster ◽  
Innovative Approaches

The chapter explains how NoSQL databases work. Since different NoSQL databases are classified into four categories (key-value, column-family, document, and graph stores), three main features of NoSQL databases are chosen, and their practical implementation is explained using examples of one or two typical NoSQL databases from each NoSQL database category. The three chosen features are: distributed storage architecture that comprises the distributed, cluster-oriented, and horizontally scalable features; consistency model that refers to the CAP and BASE features; query execution that refers to the schemaless feature. These features are chosen because, through them, it is possible to describe most of the new and innovative approaches that NoSQL databases bring to the database world.

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 When Relational-Based Applications Go to NoSQL Databases: A Survey

Information ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 241
Author(s):  
Geomar A. Schreiner ◽  
Denio Duarte ◽  
Ronaldo dos S. Melo
Keyword(s):  
Big Data ◽  
Comparative Analysis ◽  
Relational Databases ◽  
Research Area ◽  
Relational Data ◽  
Data Sets ◽  
System Architectures ◽  
Nosql Databases ◽  
State Of Art ◽  
Open Issues

Several data-centric applications today produce and manipulate a large volume of data, the so-called Big Data. Traditional databases, in particular, relational databases, are not suitable for Big Data management. As a consequence, some approaches that allow the definition and manipulation of large relational data sets stored in NoSQL databases through an SQL interface have been proposed, focusing on scalability and availability. This paper presents a comparative analysis of these approaches based on an architectural classification that organizes them according to their system architectures. Our motivation is that wrapping is a relevant strategy for relational-based applications that intend to move relational data to NoSQL databases (usually maintained in the cloud). We also claim that this research area has some open issues, given that most approaches deal with only a subset of SQL operations or give support to specific target NoSQL databases. Our intention with this survey is, therefore, to contribute to the state-of-art in this research area and also provide a basis for choosing or even designing a relational-to-NoSQL data wrapping solution.

Sign in / Sign up

Export Citation Format

Share Document