1. Amazon RDS - MySQL
   
2. Amazon RDS - MS SQL Server
   
3. Amazon RDS - Oracle
   
4. Amazon RDS - PostgreSQL
   
5. Amazon RDS - Maria DB
   
6. Amazon RDS - Amazon Aurora MySQL
   
7. Amazon RDS - Amazon Aurora PostgreSQL
8. Amazon Redshift
9. Amazon Athena
10. Microsoft Azure-MySQL
    
11. Microsoft Azure - PostgreSQL
    
12. Microsoft Azure - Maria DB
    
13. Microsoft Azure - SQL Database
    
14. Microsoft Azure - SQL Data Warehouse
15. Google Cloud SQL - MySQL
    
16. Google Cloud SQL - PostgreSQL
17. Snowflake
18. Oracle Cloud
19. IBM Cloud - DB2
20. Heroku PostgreSQL
21. Rackspace Cloud - MySQL
    
22. Rackspace Cloud - Maria DB
23. Panoply
24. MySQL
    
25. MS SQL Server
    
26. Oracle
    
27. PostgreSQL
    
28. Maria DB
    
29. MemSQL
    
30. DB2

To import data from a cloud database

1. Create a pipeline or open an existing pipeline from the Home Page, Pipelines tab or Workspaces tab and click the Add data option. You can also click the Import data option under the Workspaces tab to import data.  

Info: You can also click the Import data  icon at the top of the pipeline builder and bring data from multiple sources into the pipeline.

 

2. Select the Cloud databases category from the left pane and choose the required cloud database. You can also search cloud databases in the search box.

    

3. Choose your Database service name and Database type. 

4. Enter your Database server host.        

5. Enter your Database name, username, and password if authentication is required. 

6.  You can also select the Use SSL checkbox if your database server has been setup to serve encrypted data through SSL.

Note : The Connection name must be unique for each connection. 

7. Click Connect. 

Note:  The connection configuration will be saved for importing data in the future. Credentials are securely encrypted and stored. 

8.  Select the tables that need to be imported. You can also use SQL query to select and import data. 

9. Click Import to begin importing data from your cloud database service. 

10. Once you complete importing data, the Pipeline builder page opens and you can start applying  transforms. You can also right-click the stage and choose the Prepare data option to prepare your data using various transforms in the DataPrep Studio page. Click here to know more about the transforms. 

11. Once you are done creating your data flow and applying necessary transforms in your stages, you can right-click a stage and add a destination to complete your data flow.

Note:  After adding a destination to the pipeline, you can try executing your pipeline using a manual run at first. Once you make sure manual run works, you can then set up schedule to automate the pipeline. Learn about the different types of runs here.

To edit the cloud database connection

DataPrep saves your data connections to avoid the hassle of keying in the credentials every time you need to connect to a data source or destination. You can always edit the saved data connection and update them with new parameters or credentials using the Edit connection  option. 

1. Click Saved data connections from the Choose a data source box while creating a new dataset. 

2. You can manage your saved data connections right from the data import screen. Click the ellipsis (3 dots) icon to share, edit, view the connection overview, or remove the connection. 

3. Click the  Edit connection  option to update the saved connection with new parameters or credentials. 

SEE ALSO  

How to add a new dataset to my workspace?

How to import data using saved data connections?

How to import data from cloud storage services?

How to schedule import?

How to import data from local databases?