Get Started with Hasura DDN and Amazon Redshift

Overview

This tutorial will guide you through setting up a Hasura DDN project with Amazon Redshift. You'll learn how to:

• Set up a new Hasura DDN project
• Connect it to a Redshift database
• Generate Hasura metadata
• Create a build
• Run your first query
• Create relationships
• Mutate data

Additionally, we'll familiarize you with the steps and workflows necessary to iterate on your API.

You'll also need:

• An AWS account
• A Redshift database with namespace
• An IAM user with access to the Redshift database
• The IAM user's credentials

Prerequisites

Install the DDN CLI

Minimum version requirements

To use this guide, ensure you've installed/updated your CLI to at least v2.28.0.

macOS and Linux

Simply run the installer script in your terminal:

curl -L https://graphql-engine-cdn.hasura.io/ddn/cli/v4/get.sh | bash

ARM-based Linux Machines

Currently, the CLI does not support installation on ARM-based Linux systems.

Windows

• Download the latest DDN CLI installer for Windows.
• Run the DDN_CLI_Setup.exe installer file and follow the instructions. This will only take a minute.
• By default, the DDN CLI is installed under C:\Users\{Username}\AppData\Local\Programs\DDN_CLI
• The DDN CLI is added to your %PATH% environment variable so that you can use the ddn command from your terminal.

Install Docker

The Docker-based workflow helps you iterate and develop locally without deploying any changes to Hasura DDN, making the development experience faster and your feedback loops shorter. You'll need Docker Compose v2.20 or later.

Validate the installation

You can verify that the DDN CLI is installed correctly by running:

ddn doctor

Tutorial

Step 1. Authenticate your CLI

Before you can create a new Hasura DDN project, you need to authenticate your CLI:

ddn auth login

This will launch a browser window prompting you to log in or sign up for Hasura DDN. After you log in, the CLI will acknowledge your login, giving you access to Hasura Cloud resources.

Step 2. Scaffold out a new local project

Next, create a new local project:

ddn supergraph init my-project && cd my-project

Once you move into this directory, you'll see your project scaffolded out for you. You can view the structure by either running ls in your terminal, or by opening the directory in your preferred editor.

Step 3. Create a new Redshift database

In the AWS console, navigate to the Redshift page and create a new database called hasura_demo in your namespace. You can do so by clicking "Query data" in the top right. Then click the "+ Create" button and select database. Select the appropriate cluster / workgroup, name the database hasura_demo and click "Create database".

Step 4. Create a table in your Redshift database

Connect to your Redshift database and create the users table:

--- Create the table
CREATE TABLE users (
  id SERIAL PRIMARY KEY,
  name TEXT NOT NULL,
  age INT NOT NULL
);

--- Insert some data
INSERT INTO users (name, age) VALUES ('Alice', 25);
INSERT INTO users (name, age) VALUES ('Bob', 30);
INSERT INTO users (name, age) VALUES ('Charlie', 35);

You can verify this worked by querying all records from the users table:

SELECT * FROM users;

Step 5. Initialize your Redshift connector

In your project directory, run:

ddn connector init my_redshift -i

From the dropdown, select hasura/redshift (you can type to filter the list), and enter the value of the connection string.

ENV	Example	Description
JDBC_URL	jdbc:redshift://<host>:<port>/<database>?user=<username>&password=<password>	The JDBC URL to connect to the Amazon Redshift database.
JDBC_SCHEMAS	public,app	The schemas to use for the database. Optional. This can also be included in the connection string.

Hasura will never modify your source schema.

Step 6. Introspect your Redshift database

Next, use the CLI to introspect your Redshift database:

ddn connector introspect my_redshift

After running this, you should see a representation of your database's schema in the app/connector/my_redshift/configuration.json file; you can view this using cat or open the file in your editor.

Additionally, you can check which resources are available — and their status — at any point using the CLI:

ddn connector show-resources my_redshift

Step 7. Add your model

Now, track the table from your Redshift database as a model in your DDN metadata:

ddn model add my_redshift users

Open the app/metadata directory and you'll find a newly-generated file: Users.hml. The DDN CLI will use this Hasura Metadata Language file to represent the users table from Redshift in your API as a model.

Step 8. Create a new build

To create a local build, run:

ddn supergraph build local

The build is stored as a set of JSON files in engine/build.

Step 9. Start your local services

Start your local Hasura DDN Engine and Redshift connector:

ddn run docker-start

Your terminal will be taken over by logs for the different services.

Step 10. Run your first query

In a new terminal tab, open your local console:

ddn console --local

In the GraphiQL explorer of the console, write this query:

query {
  users {
    id
    name
    age
  }
}

You'll get the following response:

{
  "data": {
    "users": [
      {
        "id": 1,
        "name": "Alice",
        "age": 25
      },
      {
        "id": 2,
        "name": "Bob",
        "age": 30
      },
      {
        "id": 3,
        "name": "Charlie",
        "age": 35
      }
    ]
  }
}

Step 11. Iterate on your Redshift schema

Connect to your Redshift database and add a new table with some data:

-- Create the posts table
CREATE TABLE posts (
  id SERIAL PRIMARY KEY,
  user_id INT NOT NULL REFERENCES users(id) ON DELETE CASCADE,
  title TEXT NOT NULL,
  content TEXT NOT NULL,
  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

-- Insert some seed data
INSERT INTO posts (user_id, title, content) VALUES
  (1, 'My First Post', 'This is Alice''s first post.'),
  (1, 'Another Post', 'Alice writes again!'),
  (2, 'Bob''s Post', 'Bob shares his thoughts.'),
  (3, 'Hello World', 'Charlie joins the conversation.');

Verify the data by running the following query:

-- Fetch all posts with user information
SELECT
  posts.id AS post_id,
  posts.title,
  posts.content,
  posts.created_at,
  users.name AS author
FROM
  posts
JOIN
  users ON posts.user_id = users.id;

You should see a list of posts returned with the author's information joined from the users table

Step 12. Refresh your metadata and rebuild your project

tip

The following steps are necessary each time you make changes to your source schema. This includes, adding, modifying, or dropping tables.

Step 12.1. Re-introspect your data source

Run the introspection command again:

ddn connector introspect my_redshift

In app/connector/my_redshift/configuration.json, you'll see schema updated to include operations for the posts table. In app/metadata/my_redshift.hml, you'll see posts present in the metadata as well.

Step 12.2. Update your metadata

Add the posts model:

ddn model add my_redshift "posts"

Step 12.3. Create a new build

Next, create a new build:

ddn supergraph build local

Step 12.4. Restart your services

Bring down the services by pressing CTRL+C and start them back up:

ddn run docker-start

Step 13. Query your new build

Head back to your console and query the posts model:

query GetPosts {
  posts {
    id
    title
    content
  }
}

You'll get a response like this:

{
  "data": {
    "posts": [
      {
        "id": 1,
        "title": "My First Post",
        "content": "This is Alice's first post."
      },
      {
        "id": 2,
        "title": "Another Post",
        "content": "Alice writes again!"
      },
      {
        "id": 3,
        "title": "Bob's Post",
        "content": "Bob shares his thoughts."
      },
      {
        "id": 4,
        "title": "Hello World",
        "content": "Charlie joins the conversation."
      }
    ]
  }
}

Step 14. Create a relationship

Since there's already a foreign key on the posts table in Redshift, we can easily add the relationship:

ddn relationship add my_redshift "posts"

You'll see a new metadata object added to the app/metadata/posts.hml file of kind Relationship explaining the relationship between posts and users.

Step 15. Rebuild your project

As your metadata has changed, create a new build:

ddn supergraph build local

Bring down the services by pressing CTRL+C and start them back up:

ddn run docker-start

Step 16. Query using your relationship

Now, execute a nested query using your relationship:

query GetPosts {
  posts {
    id
    title
    content
    user {
      id
      name
      age
    }
  }
}

Which should return a result like this:

{
  "data": {
    "posts": [
      {
        "id": 1,
        "title": "My First Post",
        "content": "This is Alice's first post.",
        "user": {
          "id": 1,
          "name": "Alice",
          "age": 25
        }
      },
      {
        "id": 2,
        "title": "Another Post",
        "content": "Alice writes again!",
        "user": {
          "id": 1,
          "name": "Alice",
          "age": 25
        }
      },
      {
        "id": 3,
        "title": "Bob's Post",
        "content": "Bob shares his thoughts.",
        "user": {
          "id": 2,
          "name": "Bob",
          "age": 30
        }
      },
      {
        "id": 4,
        "title": "Hello World",
        "content": "Charlie joins the conversation.",
        "user": {
          "id": 3,
          "name": "Charlie",
          "age": 35
        }
      }
    ]
  }
}

Step 17. Add all commands

We'll track the available operations — for inserting, updating, and deleting — on our users and posts tables as commands.

Add all available commands:

ddn command add my_redshift "*"

You'll see newly-generated metadata files in the metadata directory for your connector that represent insert, update, and delete operations.

As your metadata has changed, create a new build:

ddn supergraph build local

Bring down the services by pressing CTRL+C and start them back up:

ddn run docker-start

Step 18. Insert new data

Create a new post for Charlie:

mutation InsertSinglePost {
  insertPosts(
    objects: {
      content: "I am an expert in Bird Law and I demand satisfaction."
      title: "Charlie has more to say"
      userId: "3"
    }
  ) {
    returning {
      id
      title
      content
      user {
        id
        name
      }
    }
  }
}

You should see a response that returns your inserted data along with the id and name fields for the author.

Next steps

Congratulations on completing your first Hasura DDN project with Redshift! 🎉

Here's what you just accomplished:

• You started with a fresh project and connected it to a local Redshift database.
• You set up metadata to represent your tables and relationships, which acts as the blueprint for your API.
• Then, you created a build — essentially compiling everything into a ready-to-use API — and successfully ran your first GraphQL queries to fetch data.
• Along the way, you learned how to iterate on your schema and refresh your metadata to reflect changes.
• Finally, we looked at how to enable mutations and insert data using your new API.

Now, you're equipped to connect and expose your data, empowering you to iterate and scale with confidence. Great work!

Take a look at our Redshift docs to learn more about how to use Hasura DDN with Redshift. Or, if you're ready, get started with adding permissions to control access to your API.