Amazon Redshift is a cloud-based data warehouse from AWS that uses SQL to analyze large datasets. It’s known for fast query performance, easy scalability, and deep integration with other AWS services. Redshift is widely used for business intelligence, analytics, and big data processing.
In a YAML file, the config section contains the following properties:
connectorname: RedShift
schemaname: <>
host: <>
port: <>
username: <>
database: <>
password: <>version: 1.0.1
destination:
plugins:
extractors:
- name: RedShift
connectorname: RedShift
schemaname: public
config:
host: hostname
port: 5439
username: user
database: database
password: password
select:
- tablenameData Hub icon on the Navigation Pane.
2. Click Add Project and provide the new project’s name.

Amazon Redshift template.
| Parameters | Description |
|---|---|
| Host: | Specify the hostname of the Amazon Redshift server. |
| Port: | Specify the port number of the Amazon Redshift server (default is 3306). |
| Username: | Provide the username to authenticate with the Amazon Redshift server. |
| Password: | Provide the password to authenticate with the Amazon Redshift server. |
| Database: | Specify the name of the Amazon Redshift database from which data will be extracted. |
| Schema Name: | Specify the Schema name for connecting to Amazon Redshift. |
| Select: | Tablename(s): Specify the table name list to load tables from the Amazon Redshift server. |
| 4. Update the details required in the template and Click Save, choose the desired destination to save the pipeline. | |
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2. For on-demand refresh, click Run Now button.
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3. The Schedule history can be checked using the history option as well as logs.
4. Click on Logs to see if the run is completed and data source is created in Bold BI.
5. Click Edit DataSource Option to view the created tables.