AWS Redshift Data Warehouse


Amazon Redshift is one of the most popular, scalable, easy to manage data warehouse options for those wanting to setup a Data Warehouse on the cloud. Read more about the features and how to get started with the popular platform from AWS here.

In case you wish to use this platform to host your data that you are aggregating using DataChannel, you can either setup a cluster of your own or use a DataChannel Managed Redshift Warehouse. This document will show you how you can connect / provision a Redshift based warehouse in minutes using the DataChannel Platform.

Self Managed Redshift Cluster

Prerequisites for connecting your Redshift Cluster
  • Create a Redshift Cluster with adequate capacity to be able to store the volume of data you anticipate storing.

  • Create a S3 bucket in the same region as your cluster and create and configure access to the bucket from your Redshift cluster. Read more here

Tips to ensure smooth functioning
  • Create a separate schema for the data coming in from DataChannel.

  • Create two users, one for loading the data and another user for reading the data from BI tools etc. This will assist you in configuring Workload Management and prevent queuing up of your queries.

Step By Step Guide

Step 1

Click on Data Warehouses tab in the left side bar navigation to reach the Data Warehouses Module as shown below.

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Step 2

Click on Add New to add a new Data Warehouse to your account.

Step 3

Select Redshift from the Storage Type drop down options.

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Step 4

Enter the details for your Redshift cluster in the form and click on Save to add the warehouse. An explanation of each of the fields in the form is given in the table below. Refer to AWS Redshift documentation here to know how to get this information for your cluster.

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Field Description



Provide a name for your warehouse. It needs to be unique across your account.



Provide the hostname or end-point for the cluster.



Provide a username which will be used to create the tables and load data. This user needs to have all rights on the schema that you intend to use. In case you are creating a dedicated schema for the data from DataChannel (which is recommended), then this user can be the schema owner.



Provide the password for the load user.

Select Users


Comma separated list of users who should get select rights on tables created by DataChannel using the schema and username specified by you.



Provide the port number for your cluster. The default value for this is 5439 unless you have changed it while creating your redshift cluster.

DB Name


Provide the name of the database you have created in your cluster.

Schema Name


Provide the database schema where DataChannel should push the data. As mentioned above, it is recommended to create a new schema for DataChannel in your database.

Use DataChannel S3


Leave this toggle off so that you can specify your own S3 bucket.

AWS Location


Provide the AWS region where your S3 bucket has been created. This should typically be same as the region in which your Redshift cluster is hosted. Example us-east-1

Bucket Name


Provide name of the S3 bucket where DataChannel should copy files before loading them into your Redshift instance. Note that DataChannel does not remove the files after they have been copied into Redshift so it is advisable to use life cycle properties to manage the removal / archival of the raw files to manage S3 costs.

Access Key


Provide the access key required to access the S3 bucket using the API. Refer AWS documentation here to learn how to manage your access keys.

Secret Key


Provide the secret key required to access the S3 bucket using the API. Refer AWS documentation here to learn how to manage your secret keys.

IAM Role


Provide the IAM role required to access the S3 bucket using the API. Refer AWS documentation here to learn how to create and manage your IAM Role.

DataChannel Managed Redshift

The process to add a DataChannel managed warehouse is very simple. Just switch the two Toggles Use DataChannel Redshift and Use DataChannel S3 to ON and click on Save.

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Still have Questions?

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