NoSQL Data Modeling

2018 ◽  
pp. 94-123
Keyword(s):  
Conceptual Model ◽  
Data Modeling ◽  
Basic Structure ◽  
Object Modeling ◽  
Similar Model ◽  
Nosql Databases ◽  
Nosql Database ◽  
Er Model ◽  
Entity Relationship ◽  
Huge Challenge

The chapter discusses the necessity for data modeling in NoSQL world. The NoSQL data modeling is a huge challenge because one of the main features of NoSQL databases is that they are schema-free, that is they allow data manipulation without the need for the previous modeling or developing an entity-relationship (ER) or similar model. Although the absence of a schema can be an advantage in some situations, with the increase in the number of NoSQL database implementations, it appears that the absence of a conceptual model can be a source of substantial problems. In order to better understand the need for data modeling in NoSQL databases, first the basic structure of an ER model and an analysis of its limitations are summarized, especially regarding an application in NoSQL databases. The concept and Object modeling notation is presented as one of the possible solutions for data modeling in NoSQL databases.

scholarly journals A Unified Conceptual Model for Data Warehouses

2021 ◽  
Vol 5 (5) ◽  
pp. 162-169
Author(s):  
Shreya Banerjee ◽  
Sourabh Bhaskar ◽  
Anirban Sarkar ◽  
Narayan C. Debnath
Keyword(s):  
Conceptual Model ◽  
Design Methodology ◽  
Data Modeling ◽  
Major Choice ◽  
Decision Makers ◽  
Systematic Design ◽  
Data Warehouses ◽  
Nosql Databases

These days, NoSQL (Not only SQL) databases are being used as a deployment tool for Data Warehouses (DW) due to its support for dynamic and scalable data modeling capabilities. Yet, decision-makers have faced several challenges to accept it as a major choice for implementation of their DW. The most significant one among those challenges is a lack of common conceptual model and a systematic design methodology for different NoSQL databases. The objective of this paper is to resolve these challenges by proposing an ontology based formal conceptual model for NoSQL based DWs. These proposed concepts are capable of realizing the cube concepts for visualization of multi-dimensional data in NoSQL based DW solutions. In this context, two strategies are specified, implemented and illustrated using a case study for devising of the proposed conceptual model.

scholarly journals NoSQL Databases and Data Modeling for a Document-oriented NoSQL Database

10.28945/2245 ◽  
2015 ◽  
Author(s):  
Robert Thomas Mason
Keyword(s):  
Data Model ◽  
Data Modeling ◽  
Data Consistency ◽  
Management Systems ◽  
Nosql Databases ◽  
Nosql Database ◽  
Logical Modeling ◽  
Foreign Key ◽  
Relational Database Management ◽  
Transactional Approach

NoSQL databases are an important component of Big Data for storing and retrieving large volumes of data. Traditional Relational Database Management Systems (RDBMS) use the ACID theorem for data consistency, whereas NoSQL Databases use a non-transactional approach called BASE. RDBMS scale vertically and NoSQL Databases can scale both horizontally (sharding) and vertically. Four types of NoSQL databases are Document-oriented, Key-Value Pairs, Column-oriented and Graph. Data modeling for Document-oriented databases is similar to data modeling for traditional RDBMS during the conceptual and logical modeling phases. However, for a physical data model, entities can be combined (denormalized) by using embedding. What was once called a foreign key in a traditional RDBMS is now called a reference in a Document-oriented NoSQL database.

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>

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 Service Data Objects (SDOs) to the Entity-Relationship (ER) Model

2012 ◽  
Vol 7 (3) ◽  
pp. 14-36
Author(s):  
Sikha Bagui ◽  
Richard Sweetman
Keyword(s):  
Conceptual Framework ◽  
Relational Model ◽  
Service Oriented Architectures ◽  
Service Oriented ◽  
Er Model ◽  
Entity Relationship ◽  
Data Objects ◽  
Service Data

In this paper the authors present a conceptual framework for translating Service Data Objects (SDOs) and XML’s SDOs to the Entity Relational (ER) Model. With the increasing dependence on service oriented architectures and the increasing need for SDOs in service oriented architectures (SOA), it is important to have a good understanding of SDOs in terms of the ER model so that SDOs can be easily converted to the relational model. In this paper they show how common SDO constructs and XML’s SDO constructs conceptually map to the ER model.

scholarly journals In the Name of the Name: RDF literals, ER attributes and the potential to rethink the structures and visualizations of catalogs

2016 ◽  
Vol 35 (2) ◽  
pp. 19 ◽  
Author(s):  
Manolis Peponakis
Keyword(s):  
Semantic Web ◽  
Conceptual Framework ◽  
Cultural Meanings ◽  
New Approach ◽  
Descriptive Information ◽  
Bibliographic Data ◽  
Er Model ◽  
Description Framework ◽  
Entity Relationship ◽  
Resource Description

<p>The aim of this study is to contribute to the field of machine-processable bibliographic data that is suitable for the Semantic Web. We examine the Entity Relationship (ER) model, which has been selected by IFLA as a “conceptual framework” in order to model the FR family (FRBR, FRAD and RDA), and the problems ER causes as we move towards the Semantic Web. Subsequently, while maintaining the semantics of the aforementioned standards but rejecting the ER as a conceptual framework for bibliographic data, this paper builds on the Resource Description Framework (RDF) potential and documents how both the RDF and Linked Data’s rationale can affect the way we model bibliographic data.</p>In this way, a new approach to bibliographic data emerges where the distinction between description and authorities is obsolete. Instead, the integration of the authorities with descriptive information becomes fundamental so that a network of correlations can be established between the entities and the names by which the entities are known. Naming is a vital issue for human cultures because names are not random sequences of characters or sounds which stand just as identifiers for the entities - they also have socio-cultural meanings and interpretations. Thus, instead of describing indivisible resources, we could describe entities that appear in a variety of names on various resources. In this study, a method is proposed to connect the names with the entities they represent and, in this way, to document the provenance of these names by connecting specific resources with specific names.

The Objects Model and the Class Diagram

2011 ◽  
pp. 13-56
Author(s):  
Peretz Shoval
Keyword(s):  
Information Needs ◽  
Relational Model ◽  
Verbal Description ◽  
Database Schema ◽  
Class Diagram ◽  
Data Types ◽  
Data Definition ◽  
Er Model ◽  
Entity Relationship ◽  
Entity Relationship Diagram

The objects model (or object oriented [OO] model) is a conceptual-application model that is used to define a database schema representing a certain reality. The model views the world as consisting of objects belonging to classes. The objects of these classes have attributes, behavior (i.e., functions), and various relationships with other objects. The objects model can be presented as a class diagram (also termed OO diagram or objects diagram). Like an entity relationship diagram (ERD), the class diagram has two main goals: 1. To serve as a communication medium between the developers (analysts/ designers) and the users or their representatives. The diagram is created as a result of the interactions between the two parties, during which they discover and define the users’ information needs; the diagram serves like a contract between these two sides which summarizes the users’ needs. 2. To be the basis for further development of the information system (IS). Based on the diagram, it should be possible to design the database schema of the application, and (partially) the functions that it will have to perform. For that, it is necessary to transform the class diagram into an equivalent verbal description—an objects schema. This is done using an object definition language (ODL), similar to data definition language (DDL) in the relational model. In principle, all components of the class diagram are mapped to the objects schema. However, the objects schema includes more details which are not included in the diagram. For example, in the diagram each attribute has a name, and some attributes may have specific constraint definitions (e.g., key, unique); in the objects schema there are more detailed definitions, including the attributes’ domains or data types (e.g., numeric, char., real, etc.) and lengths. Another example, in the class diagram, we only write the names of the classes’ functions, while in the objects schema we specify the parameters of the functions. As aforementioned, there is a great deal of similarity between the OO and ER models and diagrams, since the ER model is one of the sources from which the objects model originated. But there are differences between the two models, which we will review later on. One of these differences is that the ER model is “static,” that is, it only deals with the data structure, while the objects model also includes “behavior,” that is, the functions that operate on the data. The rest of this chapter is dedicated to describing the components of the objects model and the class diagram. The description is organized in four main categories: objects and classes, attributes, relationships, and functions.

Extended Entity Relationship Modeling

2005 ◽  
pp. 233-239 ◽  
Author(s):  
Sikha Bagui
Keyword(s):  
Comparative Analysis ◽  
Short Paper ◽  
Database Applications ◽  
Mapping Rules ◽  
Basic Concepts ◽  
Er Model ◽  
Entity Relationship ◽  
Entity Relationship Modeling

With the rising complexity of database applications, the basic concepts of Entity-Relationship (ER) modeling (as originally developed by Chen, 1976) were no longer sufficient. So the basic ER model was extended to include generalizations and specializations (Bagui & Earp, 2003; Elmasri & Navathe, 2003) and the concept of categories (Elmasri, Weeldreyer & Hevner, 1985). An ER model which includes all the concepts of the original ER model and the additional concepts of generalizations/specializations and categories is often referred to as the Extended ER (EER) model (Elmasri & Navathe, 2003). In this short paper, we shed some light on these relationship concepts, concepts that database designers often find difficult to model directly (Engels et al., 1992/1993). We also discuss the mapping rules for generalizations/specializations and categories. Important contributions in this area are also reported in (Elmasri et al., 1985; Markowitz & Shoshani, 1992; Dey, Storey & Barron, 1999; Wiederhold & Elmasri, 1980). Song, Evans, and Park (1995) also give a good comparative analysis of other types of ER diagrams and their notations.

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