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MongoDB Fundamentals

You're reading from   MongoDB Fundamentals A hands-on guide to using MongoDB and Atlas in the real world

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Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781839210648
Length 748 pages
Edition 1st Edition
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Authors (4):
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Juned Ahsan Juned Ahsan
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Juned Ahsan
Liviu Nedov Liviu Nedov
Author Profile Icon Liviu Nedov
Liviu Nedov
Amit Phaltankar Amit Phaltankar
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Amit Phaltankar
Michael Harrison Michael Harrison
Author Profile Icon Michael Harrison
Michael Harrison
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Toc

Table of Contents (15) Chapters Close

Preface
1. Introduction to MongoDB 2. Documents and Data Types FREE CHAPTER 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 13. MongoDB Case Study Appendix

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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