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CData Connect enables you to access live PostgreSQL data in workflow automation tools like Power Automate. This article shows how to integrate PostgreSQL data into a simple workflow, saving PostgreSQL data into a CSV file.
CData Connect provides a live interface for PostgreSQL, allowing you to integrate with live PostgreSQL data in Power Automate β without replicating the data. Connect uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to PostgreSQL, leveraging server-side processing to quickly return PostgreSQL data.
Connectivity to PostgreSQL from Power Automate is made possible through CData Connect AI. To work with PostgreSQL data from Power Automate, we start by creating and configuring a PostgreSQL connection.
To connect to PostgreSQL, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. If the Database property is not specified, the data provider connects to the user's default database.
You can use SSH (Secure Shell) to authenticate with PostgreSQL, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).
To connect to PostgreSQL via SSH in Password Auth mode, set the following connection properties:
To connect to PostgreSQL via SSH in Password Auth mode, set the following connection properties:
When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.
With the connection configured and a PAT generated, you are ready to connect to PostgreSQL data from Power Automate Desktop.
After configuring CData Connect with PostgreSQL, you are ready to integrate PostgreSQL data into your Power Automate workflows. Open Microsoft Power Automate, add a new flow, and name the flow.
π A new flow in Power AutomateIn the flow editor, you can add the options to connect to PostgreSQL, query PostgreSQL using SQL, and write the query results to a CSV document.
Add an "Open SQL connection" action (Action -> Database) and click the option to build the Connection string. In the Data Link Properties wizard:
After building the connection string in the Data Link Properties wizard, save the action.
π A configured 'Open SQL connection' actionAdd an "Execute SQL statement" action (Action -> Database) and configure the properties.
After configuring the properties, save the action.
π A configured 'Execute SQL statement' actionAdd a "Write to CSV file" action (Action -> File) and configure the properties.
After configuring the properties, save the action.
π A configured 'Write to CSV file' actionAdd a "Close SQL connection" action (Action -> Database) and configure the properties.
After configuring the properties, save the action.
π A configured 'Close SQL connection' actionOnce you have configured all the options for the flow, click the disk icon to save the flow. Click the play icon to run the flow.
π A fully configured workflowNow you have a workflow to save PostgreSQL data into a CSV file.
π Application data in a CSV file (Salesforce is shown)With CData Connect AI, you get live connectivity to PostgreSQL data within your Microsoft Power Automate workflows.
Now you have a direct connection to live PostgreSQL data from Power Automate tasks. You can create more connections and workflows to drive business β all without replicating PostgreSQL data.
To get SQL data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, sign up for a free trial of CData Connect AI.
This article explains how to use CData Connect AI with Power Automate Desktop. Check out our other articles for more ways to work with Power Automate (Desktop & Online):
Learn more about CData Connect AI or sign up for free trial access:
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