Working with MongoDB Atlas

Cloud databases are hosted on and often maintained by a cloud platform. The platform manages the hardware, networks, and OS, and users pay for the allocated or consumed resources. Through this course, learn what cloud-hosted databases have to offer, the factors that influence the adoption of a cloud database, and what to watch out for when using such systems. Explore the characteristics of cloud-hosted databases and the benefits and caveats of such services. Next, discover factors to consider when moving to the cloud. Finally, compare SQL and NoSQL systems and learn about some of the most powerful cloud-hosted database services. Upon completion, you'll be able to recognize the elements of different cloud databases and select the best option.

This course provides an overview of document databases, how MongoDB fits into this world, and why it is so powerful. Begin with a theoretical introduction to NoSQL databases and a look at how these differ from the traditional relational DBs. Delve into document databases, a specific type of NoSQL database, and cover their strengths and weaknesses. Next, you will look at MongoDB's architecture, how it achieves goals, such as read and write consistency, and where to apply it. You will then move on to MongoDB Atlas, the cloud-hosted version of MongoDB. Discover features, including real-time analytics and monitoring, and consider how these features allow a team to get up and running with a document database. Finally, sign up for an account with Atlas and provision a new cluster on the cloud. You will load your cluster with sample databases and connect the system from a local client application.

Storing and using data is essential for any business. You can simplify these tasks using a platform such as MongoDB and its cloud-based offering, MongoDB Atlas. In this course, you will explore various clients for MongoDB Atlas while getting hands-on with basic database tasks such as creating databases, collections, and documents. Begin by interacting with one of the sample databases on your Atlas cluster using the MongoDB Compass graphical user interface (GUI). Next, you will download and install the Atlas CLI. You will then get hands-on with the MongoDB shell. You will learn how to use it to connect to an Atlas cluster and run queries against your data. Finally, you will perform basic query operations on your Atlas cluster. You will discover simple filter operations, how specific fields in your documents can be projected in query results, and how to use the SKIP, LIMIT, and SORT operations.

In this course, you get hands-on experience with most important interactions with a MongoDB cluster: create, read, update, delete, and aggregation operations. Begin by looking at ways new documents can be added to a MongoDB collection using the Compass UI and the MongoDB shell. You will also see how to do bulk uploads from a CSV file. Next, you will use the updateOne and updateMany functions to modify one or multiple documents, carry out upsert operations, and replace documents using the replaceOne function. You will then move on to deletes and see how to perform individual and bulk deletes. You will explore types of queries and look at different ways to filter for documents, including the use of string and numeric operators and regular expressions. Finally, you will move on to aggregations in MongoDB. These allow for a whole host of operations on your data, and are accomplished by means of aggregations pipelines.

In this course, you will learn to query nested structures and documents, create indexes, and define transactions. Begin by setting up a collection with arrays, nested documents, and arrays of documents and how to query these structures. You will explore how to access array elements with the slice operator. Then you will see how to add and remove array elements and apply different operations depending on whether an array is meant to be used as a list or a set. Next, you will see how to view the query execution plan for a find operation and create a single-field index, which can help with certain types of queries. Using execution statistics, you will learn to speed up query executions by introducing an index. You will also cover the implementation of compound indexes containing multiple fields in your data. Finally, you will learn to define and execute transactions. You will work with transactions using MongoDB sessions. You will see how these can be set up to operate on a single document, or multiple documents, and how they can be rolled back in case of errors.

Final Exam: Working with MongoDB Atlas will test your knowledge and application of the topics presented throughout the Working with MongoDB Atlas journey.