The Little Mongo DB Schema Design Book
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The Little Mongo DB Schema Design Book

About the Book

The Little MongoDB Schema Design Book, covers the fundamentals off Schema design with MongoDB, as well as several useful Schema design patters for your applications.

I wrote this book to be a helpful and concise guide to MongoDB Schema design, as well as a repository to look up specific MongoDB Schema patterns. This book came around, due to my experiences teaching people about using MongoDB for application development. It tries to cover essential information that you can apply to your own applications.

We cover a lot of different aspects of Schema Design in this book. These include.

  • Schema Basics including one to one, one to many and many to many relationships
  • Embedding versus linking
  • Bucketing Strategy
  • Understanding the MongoDB MMAP and WiredTiger storage engine
  • MongoDB Indexes
  • The Metadata Schema Pattern
  • Time Series Schema Pattern
  • Queues Schema Pattern
  • Nested Categories Schema Pattern
  • Account Transactions Schema Pattern
  • Shopping Cart Schema Pattern with and without product reservation
  • A Theater Ticket Reservation Schema Pattern
  • An Embedded Array Cache Schema Pattern
  • An Internationalization Schema Pattern
  • Sharding

The book aims to provide developers with a deep but concise understanding of how to efficiently work with MongoDB.

About the Author

Christian Kvalheim
Christian Kvalheim

Christian Amor Kvalheim is a Team Lead on the developer experience team at Mongo DB Inc and is the main author of the Node.js Mongo DB driver. He came to Mongo DB from the open source community after having written his own driver for a personal project. He has been working with Mongo DB and Node.js for the last 5 years and have extensive experience in teaching Mongo DB to beginner as well as advanced developers. Before working for Mongo DB he was a team lead at Xing AG based in Barcelona, IMSI in New York and Thoughtworks in London and Chicago.

Table of Contents

  • Introduction
  • Schema Basics
  • One-To-One (1:1)
    • Model
  • One-To-Many (1:N)
    • Model
  • Many-To-Many (N:M)
    • Two Way Embedding
    • One Way Embedding
  • MMAP Storage Engine
    • Overview
    • Memory Mapped Files
    • Allocation
    • Locking
  • WiredTiger Storage Engine
    • Overview of WiredTiger
    • Essentials
    • Tuning
    • When to use WiredTiger
  • Indexes
    • Single field indexes
    • Compound indexes
    • Multi key indexes
    • Geo-spatial indexes
    • Text indexes
    • Sparse indexes
    • Unique indexes
    • Time To Live indexes
    • Covered Index Queries
  • Sharding
    • Sharding Topology
    • When to Shard
    • Choosing a Shard Key
    • Routing Shard Keys
    • Inbox Example
    • Multiple Identities Example
    • Sharding Anti-Patterns
  • Schema Design
    • Read Ratio to Write Ratio
    • Avoid Application Joins
    • Pre-aggregate Data
    • Avoid Growing Documents (MMAP)
    • Avoid Updating Whole Documents (MMAP)
    • Pre-allocated Documents (MMAP)
    • Field Names Take up Space (MMAP)
    • Over Eager Indexing
    • Custom _id Field
    • Covered Indexes
  • Queue
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Topics
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Metadata
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Materialized Path Category Hierarchy
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Covered Index Queries
    • Scaling
    • Performance
    • Notes
  • Shopping Cart with Product Reservation
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Shopping Cart with No Product Reservation
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Theater Reservation
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Account Transactions
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Time Series
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Array Slice Cache
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes
  • Internationalization
    • Schema Observations
    • Schema
    • Operations
    • Indexes
    • Scaling
    • Performance
    • Notes

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