Book Image

Mastering MongoDB 7.0 - Fourth Edition

By : Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak Abu Hammad, Elie Hannouch, Rajesh Nair, Rachelle Palmer
5 (2)
Book Image

Mastering MongoDB 7.0 - Fourth Edition

5 (2)
By: Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak Abu Hammad, Elie Hannouch, Rajesh Nair, Rachelle Palmer

Overview of this book

Mastering MongoDB 7.0 explores the latest version of MongoDB, an exceptional NoSQL database solution that aligns with the needs of modern web applications. This book starts with an informative overview of MongoDB’s architecture and developer tools, guiding you through the process of connecting to databases seamlessly. This MongoDB book explores advanced queries in detail, including aggregation pipelines and multi-document ACID transactions. It delves into the capabilities of the MongoDB Atlas developer data platform and the latest features, such as Atlas Vector Search, and their role in AI applications, enabling developers to build applications with the scalability and performance that today’s organizations need. It also covers the creation of resilient search functionality using MongoDB Atlas Search. Mastering MongoDB 7.0’s deep coverage of advanced techniques encompasses everything from role-based access control (RBAC) to user management, auditing practices, and encryption across data, network, and storage layers. By the end of this book, you’ll have developed the skills necessary to create efficient, secure, and high-performing applications using MongoDB. You’ll have the confidence to undertake complex queries, integrate robust applications, and ensure data security to overcome modern data challenges.
Table of Contents (20 chapters)
4
Chapter 4: Connecting to MongoDB

Data modeling in MongoDB

Data modeling in MongoDB is a nuanced process, distinct from traditional relational databases. On one hand, you have the demands of your application and the way users interact with it. On the other hand, there's the need for efficient performance and the specific patterns employed to access the data. Striking this balance influences the structure of the data itself, which in MongoDB is represented as documents.

Document structure

A standout feature of MongoDB is its versatile document structure. It can handle nested BSON documents and arrays up to an impressive depth of 100 levels. This depth not only showcases the flexibility of the database but also ensures data can be represented in ways that truly resonate with your application needs. Such a structure reduces the need for joins, streamlines data retrieval, and simplifies queries, making MongoDB a powerful choice for complex data architectures.

Here's a sample document, illustrating...