Book Image

MongoDB Fundamentals

By : Amit Phaltankar, Juned Ahsan, Michael Harrison, Liviu Nedov
Book Image

MongoDB Fundamentals

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.

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Table of Contents (15 chapters)
Preface
About the Book
1
1. Introduction to MongoDB
1. Introduction to MongoDB
Introduction
Database Management Systems
Introduction to MongoDB
MongoDB Editions
The MongoDB Deployment Model
Managing MongoDB
MongoDB Atlas
MongoDB Atlas Organizations, Projects, Users, and Clusters
Summary
Free Chapter
2
2. Documents and Data Types
2. Documents and Data Types
Introduction
Introduction to JSON
BSON
MongoDB Documents
MongoDB Data Types
Limits and Restrictions on Documents
Field Name Rules
Summary
3
3. Servers and Clients
3. Servers and Clients
Introduction
Network Access
Database Access
The Database Client
Server Commands
Summary
4
4. Querying Documents
4. Querying Documents
Introduction
MongoDB Query Structure
Basic MongoDB Queries
Conditional Operators
Logical Operators
Regular Expressions
Query Arrays and Nested Documents
Limiting, Skipping, and Sorting Documents
Summary
5
5. Inserting, Updating, and Deleting Documents
5. Inserting, Updating, and Deleting Documents
Introduction
Inserting Documents
Deleting Documents
Replacing Documents
Modify Fields
Update Operators
Summary
6
6. Updating with Aggregation Pipelines and Arrays
6. Updating with Aggregation Pipelines and Arrays
Introduction
Updating Array Fields
Summary
7
7. Data Aggregation
7. Data Aggregation
Introduction
aggregate Is the New find
Manipulating Data
Working with Large Datasets
Getting the Most from Your Aggregations
Summary
8
8. Coding JavaScript in MongoDB
8. Coding JavaScript in MongoDB
Introduction
Connecting to the Driver
Executing Simple Queries
Callbacks and Error Handling in Node.js
Callbacks in Node.js
Advanced Queries
Summary
9
9. Performance
9. Performance
Introduction
Query Analysis
Introduction to Indexes
Creating and Listing Indexes
Query Analysis after Indexes
Hiding and Dropping Indexes
Type of Indexes
Properties of Indexes
Other Query Optimization Techniques
Summary
10
10. Replication
10. Replication
Introduction
Client Connections
Deploying Clusters
Cluster Operations
Summary
11
11. Backup and Restore in MongoDB
11. Backup and Restore in MongoDB
Introduction
The MongoDB Utilities
Exporting MongoDB Data
Importing Data into MongoDB
Backing up an Entire Database
Restoring a MongoDB Database
Summary
12
12. Data Visualization
12. Data Visualization
Introduction
Complex Charts
Channels
Integration
Summary
13
13. MongoDB Case Study
13. MongoDB Case Study
Introduction
Fair Bay City Council
Fair Bay City Bikes
Technical Discussions and Decisions
Database Design
Use Cases
Summary
Appendix
1. Introduction to MongoDB
2. Documents and Data Types
3. Servers and Clients
4. Querying Documents
5. Inserting, Updating, and Deleting Documents
6. Updating with Aggregation Pipelines and Arrays
7. Data Aggregation
8. Coding JavaScript in MongoDB
9. Performance
10. Replication
11. Backup and Restore in MongoDB
12. Data Visualization

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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