Book Image

Mastering MongoDB 6.x - Third Edition

By : Alex Giamas
Book Image

Mastering MongoDB 6.x - Third Edition

By: Alex Giamas

Overview of this book

MongoDB is a leading non-relational database. This book covers all the major features of MongoDB including the latest version 6. MongoDB 6.x adds many new features and expands on existing ones such as aggregation, indexing, replication, sharding and MongoDB Atlas tools. Some of the MongoDB Atlas tools that you will master include Atlas dedicated clusters and Serverless, Atlas Search, Charts, Realm Application Services/Sync, Compass, Cloud Manager and Data Lake. By getting hands-on working with code using realistic use cases, you will master the art of modeling, shaping and querying your data and become the MongoDB oracle for the business. You will focus on broadly used and niche areas such as optimizing queries, configuring large-scale clusters, configuring your cluster for high performance and availability and many more. Later, you will become proficient in auditing, monitoring, and securing your clusters using a structured and organized approach. By the end of this book, you will have grasped all the practical understanding needed to design, develop, administer and scale MongoDB-based database applications both on premises and on the cloud.
Table of Contents (22 chapters)
1
Part 1 – Basic MongoDB – Design Goals and Architecture
4
Part 2 – Querying Effectively
11
Part 3 – Administration and Data Management
16
Part 4 – Scaling and High Availability

Data modeling

In this section, we will discuss the different types of data MongoDB uses, how they map to the data types that programming languages use, and how we can model data relationships in MongoDB using Ruby, Python, and PHP.

Data types

MongoDB uses BSON, a binary-encoded serialization for JSON documents. BSON extends the JSON data types, offering, for example, native data and binary data types.

BSON, compared to protocol buffers, allows for more flexible schemas, which comes at the cost of space efficiency. In general, BSON is space-efficient, easy to traverse, and time-efficient in encoding/decoding operations, as can be seen in the following table (see the MongoDB documentation at https://docs.mongodb.com/manual/reference/bson-types/):

Table 2.1 – MongoDB data types

In MongoDB, we can have documents with different value types for a given field and we can distinguish between them when querying using the $type operator.

For example...