Book Image

Learn MongoDB 4.x

By : Doug Bierer
Book Image

Learn MongoDB 4.x

By: Doug Bierer

Overview of this book

When it comes to managing a high volume of unstructured and non-relational datasets, MongoDB is the defacto database management system (DBMS) for DBAs and data architects. This updated book includes the latest release and covers every feature in MongoDB 4.x, while helping you get hands-on with building a MongoDB database app. You’ll get to grips with MongoDB 4.x concepts such as indexes, database design, data modeling, authentication, and aggregation. As you progress, you’ll cover tasks such as performing routine operations when developing a dynamic database-driven website. Using examples, you’ll learn how to work with queries and regular database operations. The book will not only guide you through design and implementation, but also help you monitor operations to achieve optimal performance and secure your MongoDB database systems. You’ll also be introduced to advanced techniques such as aggregation, map-reduce, complex queries, and generating ad hoc financial reports on the fly. Later, the book shows you how to work with multiple collections as well as embedded arrays and documents, before finally exploring key topics such as replication, sharding, and security using practical examples. By the end of this book, you’ll be well-versed with MongoDB 4.x and be able to perform development and administrative tasks associated with this NoSQL database.
Table of Contents (22 chapters)
1
Section 1: Essentials
5
Section 2: Building a Database-Driven Web Application
9
Section 3: Digging Deeper
13
Section 4: Replication, Sharding, and Security in a Financial Environment
14
Working with Complex Documents Across Collections

Developing a business rationale for sharded cluster deployment

As we mentioned earlier in this chapter, the main driving factor is the amount of data your website needs to handle. Any time you need to handle large amounts of streaming data where the data needs to be stored for later review or analysis, the size of the database could quickly increase as the number of users increases. A decision point arrives when one of two things occurs:

  • The amount of data exceeds the existing server's hard drive capacity
  • Sluggish and unacceptable performance is experienced as read and write requests are bottlenecked

Once either or both of these obstacles are encountered, you need to decide between vertical and horizontal scaling solutions. If you strongly feel that the amount of data does not increase exponentially, or if you feel that, by adding a bit more RAM, the current server could handle the load, a vertical solution might be in order. If, on the other hand, there is no end in sight...