About this course

Understand how good design facilitates scale and achieve top performance by gaining insights into indexing strategies.

About This Video

• A practical demonstration of the different storage types available to MongoDB and when to use them.
• Determine good design schemas for your collections; when to stop denormalization when designing collections.
• Indexing, next to architecture, is key in scaling your MongoDB database. Learn how, when and why to use indexing and also learn all about CRUD queries (Create, Read, Update, Delete) using the MongoDB client to put data in and get data out.

In Detail

MongoDB makes it possible to store and process large sets of data in ways that increase business value. The flexibility of unstructured, schema-less, storage, combined with robust querying and post-processing functionality, make MongoDB a compelling solution for enterprise big data needs.

We need to discuss database schemas. Yes, MongoDB is touted as schema-less but here's where we show that proper design is what allows our collections to scale. Indexing is something everyone talks about, but few understand. We'll explain MongoDB indexing, and index properties because a successful indexing strategy is a key to performance and scaling. Finally, we'll talk about CRUD commands from the MongoDB client and how to write effective queries.

Taking this course will help you understand supported standards and data types in MongoDB, and best practices to design collections to scale and index them. Also, you will learn some basic CRUD commands.

Style and Approach

Through real-world and best-practice data schemas, we show you how design impacts performance and show you how to scale your system. We demonstrate the effective use of MongoDB queries for inserting, updating, deleting, and fetching data.