Learn about designing a schema appropriately for Mongo and determining whether to embed related information or refer to it and keep items separate.
- [Instructor] When determining the schema for your database…you will come across places where you need to choose…how much data to include within each of your documents.…Mongo DB supports, as I mentioned,…a hundred levels of depth for your documents.…Obviously, this could become quite unwieldy…and very deep data structures can in fact…slow your indexing, access, and storage.…Let's take a quick look at the advantages…and disadvantages of each approach.…Embedded documents are a simpler interface to work with.…Inserting documents into a single collection…minimizes the number of operations.…
Embedded documents are easier to query and index.…Separate collections, on the other hand, require more work.…Inserting data must be done in each appropriate collection.…Reference ID's need to be used…to access appropriate items.…And aggregating related data…can require multiple operations.…This can be a little difficult…to think about in the abstract.…So, let's work through a use case…and see what choices we might make…and how they would affect the interaction.…
- Installing MongoDB for Windows and OS X
- Why Mongo?
- Document-oriented data
- Exploring the Mongo shell
- Importing data into the database
- Building an application in Node.js
- Tuning Mongo queries
- Replication and sharding
Skill Level Intermediate
1. Understand MongoDB
2. Explore the System
3. Build an Application in Node
Node MongoDB setup4m 59s
4. Advanced Topics
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.