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MongoDB Fundamentals

MongoDB Fundamentals

By : Amit Phaltankar , Juned Ahsan , Michael Harrison , Liviu Nedov
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MongoDB Fundamentals

MongoDB Fundamentals

5 (24)
By: Amit Phaltankar , Juned Ahsan , Michael Harrison , Liviu Nedov

Overview of this book

MongoDB is one of the most popular database technologies for handling large collections of data. This book will help MongoDB beginners develop the knowledge and skills to create databases and process data efficiently. Unlike other MongoDB books, MongoDB Fundamentals dives into cloud computing from the very start – showing you how to get started with Atlas in the first chapter. You will discover how to modify existing data, add new data into a database, and handle complex queries by creating aggregation pipelines. As you progress, you'll learn about the MongoDB replication architecture and configure a simple cluster. You will also get to grips with user authentication, as well as techniques for backing up and restoring data. Finally, you'll perform data visualization using MongoDB Charts. You will work on realistic projects that are presented as bitesize exercises and activities, allowing you to challenge yourself in an enjoyable and attainable way. Many of these mini-projects are based around a movie database case study, while the last chapter acts as a final project where you will use MongoDB to solve a real-world problem based on a bike-sharing app. By the end of this book, you'll have the skills and confidence to process large volumes of data and tackle your own projects using MongoDB.
Table of Contents (15 chapters)
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Preface

Database Management Systems

A Database Management System (DBMS) provides the ability to store and retrieve data. It uses query languages to create, update, delete, and retrieve data. Let us look at the different types of DBMS.

Relational Database Management Systems

Relational Database Management Systems (RDBMS) are used to store structured data. The data is stored in the form of tables that consist of rows and columns. The tables can have relationships with other tables to depict the actual data relationships. For example, in a university relational database, the Student table can be related to the Course and Marks Obtained tables through a common columns such as courseId.

NoSQL Database Management Systems

NoSQL databases were invented to solve the problem of storing unstructured and semi-structured data. Relational databases enforce the structure of data to be defined before the data can be stored. This database structure definition is often referred to as schema, which pertains to the data entities, that is, its attributes and types. RDBMS client applications are tightly coupled with the schema. It is hard to modify the schema without affecting the clients. Contrastingly, NoSQL databases allow you to store the data without a schema and also support dynamic schema, which decouples the clients from a rigid schema, and is often necessary for modern and experimental applications.

The data stored in the NoSQL database varies depending on the provider, but generally, data is stored as documents instead of tables. An example of this would be databases for inventory management, where different products can have different attributes and, therefore, require a flexible structure. Similarly, an analytics database that stores data from different sources in different structures would also need a flexible structure.

Comparison

Let us compare NoSQL databases and RDBMS based on the following factors. You will get an in-depth understanding of these as you read through this book. For now, a basic overview is provided in the following table:

Figure 1.1: Differences between relational databases and NoSQL

Figure 1.1: Differences between relational databases and NoSQL

That concludes our discussion on databases and the differences between the various database types. In the next section, we will begin our exploration of MongoDB.

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MongoDB Fundamentals
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