Data Modeling With Nosql Database

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Data Modeling With Nosql Database

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Author : Sultan Ahmad
language : en
Publisher:
Release Date : 2021-03-30

Data Modeling With Nosql Database written by Sultan Ahmad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-30 with categories.

● An important step in database implementation is the data modeling, because it facilitates the understanding of the project through key features that can prevent programming and operation errors. ● In database technologies, some of the new issues increasingly debated arenon-conventional applications, including NoSQL (Not only SQL) databases, whichwere initially created in response to the needs for better scalability, lowerlatency and higher flexibility in an era of bigdata and cloud computing. Thesenon-functional aspects are the main reason for using NoSQL database. ● Data modeling has an important role to play in NoSQL environments. The datamodeling process involves the creation of a diagram that represents the meaning of the data and the relationship between the data elements. Thus, understanding is a fundamental aspect of data modeling and a pattern for this kind of representation has few contributions for NoSQL databases. ● This book explains a NoSQL data modeling standard, introducing modeling techniques that can be used on document-oriented databases. We have considered Cassandra and Riak NoSQL databases because of the heterogeneous characteristics of each NoSQL database classification so that to fill the knowledge gap by studying the available non-relational databases in order to develop a systematic approach for solving problems of data persistence using these technologies. Ajit & Sultan.......

Data Modeling With Nosql Database

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Author : Ajit Singh
language : en
Publisher: Independently Published
Release Date : 2022-11-06

Data Modeling With Nosql Database written by Ajit Singh and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-06 with categories.

● An important step in database implementation is the data modeling, because it facilitates the understanding of the project through key features that can prevent programming and operation errors. ● In database technologies, some of the new issues increasingly debated are non-conventional applications, including NoSQL (Not only SQL) databases, which were initially created in response to the needs for better scalability, lower latency and higher flexibility in an era of bigdata and cloud computing. These non-functional aspects are the main reason for using NoSQL database. ● Data modeling has an important role to play in NoSQL environments. The data modeling process involves the creation of a diagram that represents the meaning of the data and the relationship between the data elements. Thus, understanding is a fundamental aspect of data modeling and a pattern for this kind of representation has few contributions for NoSQL databases. ● This edition (3rd) explains a NoSQL data modeling standard, introducing modeling techniques that can be used on document-oriented databases. We have considered Cassandra and Riak NoSQL databases because of the heterogeneous characteristics of each NoSQL database classification so that to fill the knowledge gap by studying the available non-relational databases in order to develop a systematic approach for solving problems of data persistence using these technologies. Ajit.............

Graph Data Modeling For Nosql And Sql

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Author : Thomas Frisendal
language : en
Publisher:
Release Date : 2016

Graph Data Modeling For Nosql And Sql written by Thomas Frisendal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Database management categories.

Master a graph data modeling technique superior to traditional data modeling for both relational and NoSQL databases (graph, document, key-value, and column), leveraging cognitive psychology to improve big data designs. From Karen Lopez's Foreword: In this book, Thomas Frisendal raises important questions about the continued usefulness of traditional data modeling notations and approaches: Are Entity Relationship Diagrams (ERDs) relevant to analytical data requirements? Are ERDs relevant in the new world of Big Data? Are ERDs still the best way to work with business users to understand their needs? Are Logical and Physical Data Models too closely coupled? Are we correct in using the same notations for communicating with business users and developers? Should we refine our existing notations and tools to meet these new needs, or should we start again from a blank page? What new notations and approaches will we need? How will we use those to build enterprise database systems? Frisendal takes us through the history of data modeling, enterprise data models and traditional modeling methods. He points out, quite contentiously, where he feels we have gone wrong and in a few places where we got it right. He then maps out the psychology of meaning and context, while identifying important issues about where data modeling may or may not fit in business modeling. The main subject of this work is a proposal for a new exploration-driven modeling approach and new modeling notations for business concept models, business solutions models, and physical data models with examples on how to leverage those for implementing into any target database or datastore. These new notations are based on a property graph approach to modeling data. From the author's introduction: This book proposes a new approach to data modeling-one that "turns the inside out". For well over thirty years, relational modeling and normalization was the name of the game. One can ask that if normalization was the answer, what was the problem? There is something upside-down in that approach, as we will see in this book. Data analysis (modeling) is much like exploration. Almost literally. The data modeler wanders around searching for structure and content. It requires perception and cognitive skills, supported by intuition (a psychological phenomenon), that together determine how well the landscape of business semantics is mapped. Mapping is what we do; we explore the unknowns, draw the maps and ...

Nosql And Sql Data Modeling

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Author : Ted Hills
language : en
Publisher:
Release Date : 2016

Nosql And Sql Data Modeling written by Ted Hills and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Database management categories.

How do we design for data when traditional design techniques cannot extend to new database technologies? In this era of big data and the Internet of Things, it is essential that we have the tools we need to understand the data coming to us faster than ever before, and to design databases and data processing systems that can adapt easily to ever-changing data schemas and ever-changing business requirements. There must be no intellectual disconnect between data and the software that manages it. It must be possible to extract meaning and knowledge from data to drive artificial intelligence applications. Novel NoSQL data organization techniques must be used side-by-side with traditional SQL databases. Are existing data modeling techniques ready for all of this? The Concept and Object Modeling Notation (COMN) is able to cover the full spectrum of analysis and design. A single COMN model can represent the objects and concepts in the problem space, logical data design, and concrete NoSQL and SQL document, key-value, columnar, and relational database implementations. COMN models enable an unprecedented level of traceability of requirements to implementation. COMN models can also represent the static structure of software and the predicates that represent the patterns of meaning in databases. This book will teach you: the simple and familiar graphical notation of COMN with its three basic shapes and four line styles how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren't tangled with confused techno-speak how to express logical data designs that are freer from implementation considerations than is possible in any other notation how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms how to use COMN to specify physical database implementations in any NoSQL or SQL database with the precision necessary for model-driven development "I believe that this is a breakthrough modeling technique - and it is technique, not just notation. COMN provides notation to handle all of the constructs that E-R techniques don't do well, and it steps up to the problem of linking physical and conceptual models. ... I'm convinced that COMN is the future of data modeling." Dave Wells, BI and Analytics Educator and Consultant, Infocentric

Sql Nosql Databases

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Author : Andreas Meier
language : en
Publisher: Springer
Release Date : 2019-07-05

Sql Nosql Databases written by Andreas Meier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-05 with Computers categories.

This book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations. The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types: SQL and NoSQL databases, and their respective management systems The nature and uses of Big Data A high-level view of the organization of data management Data Modeling and Consistency Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. Coverage of languages extends from an overview of operators, to SQL and and QBE (Query by Example), to integrity constraints and more. A full chapter probes the challenges of Ensuring Data Consistency, covering: Multi-User Operation Troubleshooting Consistency in Massive Distributed Data Comparison of the ACID and BASE consistency models, and more System Architecture also gets from its own chapter, which explores Processing of Homogeneous and Heterogeneous Data; Storage and Access Structures; Multi-dimensional Data Structures and Parallel Processing with MapReduce, among other topics. Post-Relational and NoSQL Databases The chapter on post-relational databases discusses the limits of SQL – and what lies beyond, including Multi-Dimensional Databases, Knowledge Bases and and Fuzzy Databases. A final chapter covers NoSQL Databases, along with Development of Non-Relational Technologies, Key-Value, Column-Family and Document Stores XML Databases and Graphic Databases, and more The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. SQL & NoSQL Databases conveys the strengths and weaknesses of relational and non-relational approaches, and shows how to undertake development for big data applications. The book benefits readers including students and practitioners working across the broad field of applied information technology. This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.

Nosql For Mere Mortals

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Author : Dan Sullivan
language : en
Publisher: Addison-Wesley Professional
Release Date : 2015-04-06

Nosql For Mere Mortals written by Dan Sullivan and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-06 with Computers categories.

The Easy, Common-Sense Guide to Solving Real Problems with NoSQL The Mere Mortals® tutorials have earned worldwide praise as the clearest, simplest way to master essential database technologies. Now, there’s one for today’s exciting new NoSQL databases. NoSQL for Mere Mortals guides you through solving real problems with NoSQL and achieving unprecedented scalability, cost efficiency, flexibility, and availability. Drawing on 20+ years of cutting-edge database experience, Dan Sullivan explains the advantages, use cases, and terminology associated with all four main categories of NoSQL databases: key-value, document, column family, and graph databases. For each, he introduces pragmatic best practices for building high-value applications. Through step-by-step examples, you’ll discover how to choose the right database for each task, and use it the right way. Coverage includes --Getting started: What NoSQL databases are, how they differ from relational databases, when to use them, and when not to Data management principles and design criteria: Essential knowledge for creating any database solution, NoSQL or relational --Key-value databases: Gaining more utility from data structures --Document databases: Schemaless databases, normalization and denormalization, mutable documents, indexing, and design patterns --Column family databases: Google’s BigTable design, table design, indexing, partitioning, and Big Data Graph databases: Graph/network modeling, design tips, query methods, and traps to avoid Whether you’re a database developer, data modeler, database user, or student, learning NoSQL can open up immense new opportunities. As thousands of database professionals already know, For Mere Mortals is the fastest, easiest route to mastery.

Data Modeling For Azure Data Services

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Author : Peter ter Braake
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-30

Data Modeling For Azure Data Services written by Peter ter Braake and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-30 with Computers categories.

Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guide Key FeaturesDesign a cost-effective, performant, and scalable database in AzureChoose and implement the most suitable design for a databaseDiscover how your database can scale with growing data volumes, concurrent users, and query complexityBook Description Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution. What you will learnModel relational database using normalization, dimensional, or Data Vault modelingProvision and implement Azure SQL DB and Azure Synapse SQL PoolsDiscover how to model a Data Lake and implement it using Azure StorageModel a NoSQL database and provision and implement an Azure Cosmos DBUse Azure Data Factory to implement ETL/ELT processesCreate a star schema model using dimensional modelingWho this book is for This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.

Sql And Nosql Databases

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Author : Michael Kaufmann
language : en
Publisher: Springer Nature
Release Date : 2023-06-29

Sql And Nosql Databases written by Michael Kaufmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-29 with Computers categories.

This textbook offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques and examine upcoming innovations. In the first five chapters, the authors analyze in detail the management, modeling, languages, security, and architecture of relational databases, graph databases, and document databases. Moreover, an overview of other SQL- and NoSQL-based database approaches is provided. In addition to classic concepts such as the entity and relationship model and its mapping in SQL database schemas, query languages or transaction management, other aspects for NoSQL databases such as non-relational data models, document and graph query languages (MQL, Cypher), the Map/Reduce procedure, distribution options (sharding, replication) or the CAP theorem (Consistency, Availability, Partition Tolerance) are explained. This 2nd English edition offers a new in-depth introduction to document databases with a method for modeling document structures, an overview of the document-oriented MongoDB query language MQL as well as security and architecture aspects. The topic of database security is newly introduced as a separate chapter and analyzed in detail with regard to data protection, integrity, and transactions. Texts on data management, database programming, and data warehousing and data lakes have been updated. In addition, the book now explains the concepts of JSON, JSON schema, BSON, index-free neighborhood, cloud databases, search engines and time series databases. The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. It conveys an in-depth comparison of relational and non-relational approaches and shows how to undertake development for big data applications. This way, it benefits students and practitioners working across the broad field of data science and applied information technology.

Data Modeling For Mongodb

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Author : Steve Hoberman
language : en
Publisher: Technics Publications
Release Date : 2014-06-01

Data Modeling For Mongodb written by Steve Hoberman and has been published by Technics Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-01 with Computers categories.

Congratulations! You completed the MongoDB application within the given tight timeframe and there is a party to celebrate your application’s release into production. Although people are congratulating you at the celebration, you are feeling some uneasiness inside. To complete the project on time required making a lot of assumptions about the data, such as what terms meant and how calculations are derived. In addition, the poor documentation about the application will be of limited use to the support team, and not investigating all of the inherent rules in the data may eventually lead to poorly-performing structures in the not-so-distant future. Now, what if you had a time machine and could go back and read this book. You would learn that even NoSQL databases like MongoDB require some level of data modeling. Data modeling is the process of learning about the data, and regardless of technology, this process must be performed for a successful application. You would learn the value of conceptual, logical, and physical data modeling and how each stage increases our knowledge of the data and reduces assumptions and poor design decisions. Read this book to learn how to do data modeling for MongoDB applications, and accomplish these five objectives: Understand how data modeling contributes to the process of learning about the data, and is, therefore, a required technique, even when the resulting database is not relational. That is, NoSQL does not mean NoDataModeling! Know how NoSQL databases differ from traditional relational databases, and where MongoDB fits. Explore each MongoDB object and comprehend how each compares to their data modeling and traditional relational database counterparts, and learn the basics of adding, querying, updating, and deleting data in MongoDB. Practice a streamlined, template-driven approach to performing conceptual, logical, and physical data modeling. Recognize that data modeling does not always have to lead to traditional data models! Distinguish top-down from bottom-up development approaches and complete a top-down case study which ties all of the modeling techniques together. This book is written for anyone who is working with, or will be working with MongoDB, including business analysts, data modelers, database administrators, developers, project managers, and data scientists. There are three sections: In Section I, Getting Started, we will reveal the power of data modeling and the tight connections to data models that exist when designing any type of database (Chapter 1), compare NoSQL with traditional relational databases and where MongoDB fits (Chapter 2), explore each MongoDB object and comprehend how each compares to their data modeling and traditional relational database counterparts (Chapter 3), and explain the basics of adding, querying, updating, and deleting data in MongoDB (Chapter 4). In Section II, Levels of Granularity, we cover Conceptual Data Modeling (Chapter 5), Logical Data Modeling (Chapter 6), and Physical Data Modeling (Chapter 7). Notice the “ing” at the end of each of these chapters. We focus on the process of building each of these models, which is where we gain essential business knowledge. In Section III, Case Study, we will explain both top down and bottom up development approaches and go through a top down case study where we start with business requirements and end with the MongoDB database. This case study will tie together all of the techniques in the previous seven chapters. Nike Senior Data Architect Ryan Smith wrote the foreword. Key points are included at the end of each chapter as a way to reinforce concepts. In addition, this book is loaded with hands-on exercises, along with their answers provided in Appendix A. Appendix B contains all of the book’s references and Appendix C contains a glossary of the terms used throughout the text.

Nosql Data Models

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Author : Olivier Pivert
language : en
Publisher: John Wiley & Sons
Release Date : 2018-07-30

Nosql Data Models written by Olivier Pivert and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-30 with Computers categories.

The topic of NoSQL databases has recently emerged, to face the Big Data challenge, namely the ever increasing volume of data to be handled. It is now recognized that relational databases are not appropriate in this context, implying that new database models and techniques are needed. This book presents recent research works, covering the following basic aspects: semantic data management, graph databases, and big data management in cloud environments. The chapters in this book report on research about the evolution of basic concepts such as data models, query languages, and new challenges regarding implementation issues.