Book Image

Mastering MongoDB 7.0 - Fourth Edition

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

Mastering MongoDB 7.0 - Fourth Edition

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

Geospatial features in MongoDB

Geospatial features in MongoDB are designed to support the creation of location-aware applications and facilitate location-based queries, catering to a diverse range of users. Through its specialized indexes and operators, MongoDB can efficiently manage geographical data, which makes it suitable for a wide range of applications, such as maps and location searching.

Legacy coordinate pairs are the traditional way of representing locations using two-element arrays with the longitude first and then the latitude. For example, [ -73.97, 40.77 ] represents a point in New York City. When indexing such data, you can use the 2d index type. Following is an example of creating index for legacy coordinate pairs:

db.collection.createIndex({ loc: "2d" })

GeoJSON objects

GeoJSON objects are of three types:

  • Point: Represents a single point in space with longitude and latitude coordinates
  • LineString: A series of two or more points that...