Name: Creating your first FaunaDB database
Uploaded: 2019-09-26T21:36:11-05:00
Description: We walk through creating a new Database in the FaunaDB console complete with some demo data. We do some exploration of the data, introducing concepts like Collections and Indexes, before showing an example FQL query that runs against the database. This sets us up to talk about FQL in future videos

An Introduction to FaunaDB

Creating your first FaunaDB database

Overview of the FaunaDB Query Language (FQL)

Getting fields out of Refs with Get

FQL Page objects can be arguments to Array functions

Paginating and passing other options with Paginate

Using FQL Lambda in Array functions

Accessing fields through Refs with Select

Creating an access token and choosing a role for it

Inserting a document

Selecting multiple fields in an FQL query

Installing the FaunaDB CLI and using it to send queries from a local file

Reducing the number of read ops in a query using indexes

Orchestrating multiple dependent expressions in the same transaction with Do

Introduction to FaunaDB's GraphQL support

The Complete Guide to FaunaDB

We walk through creating a new Database in the FaunaDB console complete with some demo data. We do some exploration of the data, introducing concepts like Collections and Indexes, before showing an example FQL query that runs against the database. This sets us up to talk about FQL in future videos

https://app.egghead.io/api/v1/lessons/faunadb-creating-your-first-faunadb-database/subtitles

Instructor: [00:00] Once you've signed up for a Fauna account, you'll end up at the dashboard. Since I already have a database in my account, I see it right here along with the readops, the writeops, storage, and data transfer.

[00:10] To create a new database, we'll click create new database. We'll give our database a name and let Fauna prepopulate it with demo data. This demo data creates a warehouse data structure for us.

[00:30] Now that we've created our database with the demo data, we can see that there are a number of collections and a number of indexes. If we look at the customers collection, we can see a number of objects or documents. These documents can be explored through the UI.

[00:44] Indexes are groups of documents inside of each of our collections. In this case, we have indexes that represent all the objects in each of our collections. If we go to the shell on the FaunaDB console, we can use FQL to write a query.

[00:59] This query matches on the index all customers, paginates the results, selects the data from the pagination, and maps over the results of the pagination using a Lambda. Since in the Lambda, the argument is a ref, we have to get the object.

[01:17] Finally, we select the first name from all of the data. If we run this query, we can see that we do indeed get all first names.

Creating your first FaunaDB database

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The Complete Guide to FaunaDB