Creating Relationships

In the previous lesson, you learned how to create nodes using the Data Importer. In this lesson, you will learn how to create relationships between nodes.

Creating Relationships in Data Importer

Relationships connect nodes and represent how data is connected. In the Northwind model, relationships include:

Customer -[:PLACED]→ Order
Order -[:CONTAINS]→ Product
Product -[:IN_CATEGORY]→ Category
Supplier -[:SUPPLIES]→ Product

Step 1: Create Nodes First

Ensure all node types exist first:

Add all node labels: Customer, Order, Product, Category, Supplier, and others
Map properties from CSV files
Set unique identifiers for each node type

Step 2: Draw a Relationship

In the Data Importer canvas:

Hover over the edge of the source node until you see the + icon
Drag from the source node to the target node
Release to create the relationship

Creating a relationship in Data Importer

Step 3: Configure the Relationship

In the Definition panel:

Enter the relationship type such as PLACED, CONTAINS, or IN_CATEGORY
Select the data source — the CSV file — that contains the relationship data
Map the From ID - the column that matches the source node’s unique identifier
Map the To ID - the column that matches the target node’s unique identifier
Optionally map relationship properties from additional columns

Green checkmarks indicate valid mappings

The Data Importer shows a green checkmark when an element has been mapped correctly. If you see a warning, check that:

The ID columns match the unique identifiers on the nodes
The data types are compatible
The CSV file contains the expected columns

Step 4: Add Relationship Properties

Some relationships carry additional data. For example, the CONTAINS relationship between Order and Product includes:

quantity - how many units were ordered
unitPrice - the price at the time of order
discount - any discount applied

To add relationship properties:

Select the relationship in the model
Click Map from table
Select the columns to include as properties
Set appropriate data types

Example: Northwind Relationships

For the Northwind dataset, create these relationships:

From	Relationship	To	Properties
Customer	PLACED	Order	(none)
Order	CONTAINS	Product	quantity, unitPrice, discount
Product	IN_CATEGORY	Category	(none)
Supplier	SUPPLIES	Product	(none)
Employee	PROCESSED	Order	(none)
Order	SHIPPED_BY	Shipper	(none)
Employee	REPORTS_TO	Employee	(none)

From

Relationship

Properties

Customer

PLACED

Order

(none)

Order

CONTAINS

Product

quantity, unitPrice, discount

Product

IN_CATEGORY

Importing Nodes and Relationships from a Single File

Northwind uses separate CSV files per table, but you often encounter denormalized or joined data where one file contains both node and relationship data.

Example: A ratings.csv file with movieId, userId, name, rating, timestamp can create both User nodes and RATED relationships to Movie nodes.

The process is the same as with multiple files:

Upload the single CSV file to Data Importer
Create the node label and relationship in the model
Map the same file as the data source for both the node and the relationship
Map node columns (e.g. userId, name) to the User node, and relationship columns (e.g. rating, timestamp) to the RATED relationship
Set the Node ID mappings: From userId (User) and To movieId (Movie)
Run the import

When the source combines entity and linkage data, Data Importer creates the nodes and relationships in one pass. Ensure the file has columns for both the node identifier and the relationship target identifier.

Verify Relationships

Verify relationships:

cypher

// Count relationships by type
MATCH ()-[r]->()
RETURN type(r) AS relationship, COUNT(*) AS count
ORDER BY count DESC

cypher

// Sample a specific relationship
MATCH (c:Customer)-[r:PLACED]->(o:Order)
RETURN c.companyName, o.orderID
LIMIT 5

cypher

// Check relationship properties
MATCH (o:Order)-[r:CONTAINS]->(p:Product)
RETURN o.orderID, p.productName, r.quantity, r.unitPrice
LIMIT 5

Using the Data Importer

With AuraDB, the Data Importer is integrated:

Open your instance and click Import
Design your model with nodes and relationships
Click Run import to execute

Check Your Understanding

Relationship ID Mapping

When creating a relationship in the Data Importer, what must you map to connect two nodes?

❏ The node labels
❏ The relationship properties
✓ The unique identifiers (IDs) of the source and target nodes
❏ The CSV file name

Hint

Relationships connect nodes using their unique identifiers. The Data Importer needs to know which column in the CSV matches the ID on each node.

Solution

You must map the unique identifiers (IDs) of the source and target nodes. The Data Importer uses these IDs to find the correct nodes and create the relationship between them.

For example, to create a PLACED relationship between Customer and Order, you map:

From ID: The column containing customer IDs (matching Customer’s unique identifier)
To ID: The column containing order IDs (matching Order’s unique identifier)

Summary

In this lesson, you learned how to create relationships in the Data Importer by:

Drawing connections between nodes
Mapping ID columns to link nodes
Adding relationship properties

In the next lesson, you will learn how to handle complex data scenarios during import.

Importing Relational Data into Neo4j

Foundation

Designing the Graph Model

Importing Data

Validating and Querying

Creating Relationships