Learn Mongoose, Neo4j and Particle

In this course we will learn some of the basics of getting data into and out of Neo4J, as well as touch on some of the libraries and tooling available in the Neo4J community ecosystem, which we will leverage to quickly create and use a full-featured GraphQL API.

We will start by learning how to run and interact with Neo4J locally. Then we will develop a graph model in which to store the data that we pull from SWAPI via REST. We will then create an Apollo GraphQL API driven by a few simple schemas which fit into this model. We will then write some simple code to crawl SWAPI and insert the data into Neo4J through our GraphQL API. Once there is data in the store, we will learn about some of the features in `neo4j-graphql-js` that make connecting and accessing our graph Nodes easier.

Neo4j delivers the lightning-fast read and write performance you need. Neo4j combines native graph storage, scalable architecture optimized for speed, and ACID compliance to ensure predictability of relationship-based queries.

neo4j

Build a Neo4J & GraphQL API

Express is a minimal and flexible Node.js web application framework that provides a robust set of features for web and mobile applications.

express

Mongoose allows you to easily select resources by ID from your MongoDB. This is an important aspect to creating an API.

Select by ID with Mongoose and Express

particle

Before powering up the Particle Photon we are going to look at what each of the components are on the board.

Particle Photon Component Overview

There are different types of data in Neo4J: Nodes and Relationships. We will cover the ways to create each type of data: creating nodes with properties, creating nodes with relationships, and creating constraints on nodes and relationships.

Create Nodes and Relationships in Neo4J with Cypher

Once there is data in Neo4J, we need to be able to access it. We will cover the structure of a cypher query to return parts of our graph.

Read Nodes and Relationships in Neo4J with Cypher

The data in our graph is unlikely to stay the same forever. We will cover the syntax used to find and modify existing data in different ways through the use of parameters.

Update Nodes and Relationships in Neo4J with Cypher

Nothing lives forever, so we need to know how to use DELETE and DETACH to get rid of nodes and relationships we no longer want in our graph.

Delete Nodes and Relationships in Neo4J with Cypher

We will learn about `neo4j-graphql-js` and how to leverage it to quickly create a full-featured API backed by Neo4J. We will create a few simple schemas to represent our model.

Use neo4j-graphql-js to Create a Simple API

We will learn to use the `@relation` directive provided by `neo4j-graphql-js` to make the relationships in our model explicit in our schemas.

Explicitly Model Schema Relationships with the @relation Directive in neo4j-graphql-js

We will use automatically generated mutations in a Apollo GraphQL API augmented with `neo4j-graphql-js` to insert data that we get from SWAPI into Neo4J.

Create Data in Neo4J Through a GraphQL API

We will use the `@cypher` directive provided by `neo4j-graphql-js` to return data about how nodes are related to each other in our schemas without writing custom resolvers.


Build Complex Schema Relationships with the @cypher Directive in neo4j-graphql-js

We will use our own custom mutations in an Apollo GraphQL API to update or create data that we scrape from SWAPI into Neo4J with. We will use the `@cypher` directive to use custom merge statements in these mutations.


Create Custom GraphQL Mutations with the @cypher Directive in neo4j-graphql-js

Mongoose provides a straight-forward, schema-based solution to model your application data. It includes built-in type casting, validation, query building, business logic hooks and more, out of the box.

mongoose

One of the great things about NoSQL databases is that you do not have to decide on your data schema while developing. As you get closer to production though, you'll often want to more clearly define the shape of the data you are working with.

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