How to connect Microsoft SQL Server and PostgreSQL
Create a New Scenario to Connect Microsoft SQL Server and PostgreSQL
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Microsoft SQL Server, triggered by another scenario, or executed manually (for testing purposes). In most cases, Microsoft SQL Server or PostgreSQL will be your first step. To do this, click "Choose an app," find Microsoft SQL Server or PostgreSQL, and select the appropriate trigger to start the scenario.

Add the Microsoft SQL Server Node
Select the Microsoft SQL Server node from the app selection panel on the right.


Microsoft SQL Server

Configure the Microsoft SQL Server
Click on the Microsoft SQL Server node to configure it. You can modify the Microsoft SQL Server URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the PostgreSQL Node
Next, click the plus (+) icon on the Microsoft SQL Server node, select PostgreSQL from the list of available apps, and choose the action you need from the list of nodes within PostgreSQL.


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Authenticate PostgreSQL
Now, click the PostgreSQL node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your PostgreSQL settings. Authentication allows you to use PostgreSQL through Latenode.
Configure the Microsoft SQL Server and PostgreSQL Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Microsoft SQL Server and PostgreSQL Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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AI Anthropic Claude 3
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Trigger on Webhook
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Webhook response


Save and Activate the Scenario
After configuring Microsoft SQL Server, PostgreSQL, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Microsoft SQL Server and PostgreSQL integration works as expected. Depending on your setup, data should flow between Microsoft SQL Server and PostgreSQL (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Microsoft SQL Server and PostgreSQL
Microsoft SQL Server + PostgreSQL + Google Sheets: When a new or updated row occurs in Microsoft SQL Server, the data is migrated to PostgreSQL. The success or failure of the migration is then logged as a new row in Google Sheets for reporting.
PostgreSQL + Microsoft SQL Server + Slack: When a new or updated row occurs in PostgreSQL, the data is synchronized to Microsoft SQL Server. If the synchronization fails (e.g., due to data type mismatch), a notification is sent to database administrators in Slack.
Microsoft SQL Server and PostgreSQL integration alternatives

About Microsoft SQL Server
Use Microsoft SQL Server in Latenode to automate database tasks. Directly query, update, or insert data in response to triggers. Sync SQL data with other apps; simplify data pipelines for reporting and analytics. Build automated workflows without complex coding to manage databases efficiently and scale operations.
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About PostgreSQL
Use PostgreSQL in Latenode to automate database tasks. Build flows that react to database changes or use stored data to trigger actions in other apps. Automate reporting, data backups, or sync data across systems without code. Scale complex data workflows easily within Latenode's visual editor.
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See how Latenode works
FAQ Microsoft SQL Server and PostgreSQL
How can I connect my Microsoft SQL Server account to PostgreSQL using Latenode?
To connect your Microsoft SQL Server account to PostgreSQL on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Microsoft SQL Server and click on "Connect".
- Authenticate your Microsoft SQL Server and PostgreSQL accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I synchronize product catalogs between databases?
Yes, you can! Latenode simplifies data synchronization with its visual editor and JavaScript support, automating updates and ensuring consistent product information across Microsoft SQL Server and PostgreSQL.
What types of tasks can I perform by integrating Microsoft SQL Server with PostgreSQL?
Integrating Microsoft SQL Server with PostgreSQL allows you to perform various tasks, including:
- Migrating data between Microsoft SQL Server and PostgreSQL databases.
- Backing up Microsoft SQL Server data to a PostgreSQL instance.
- Synchronizing user data between both databases.
- Creating reports by combining data from both sources.
- Triggering alerts based on data changes.
Can I use JavaScript to transform data between databases?
Yes, Latenode allows using JavaScript code blocks for complex data transformations, ensuring seamless integration between Microsoft SQL Server and PostgreSQL.
Are there any limitations to the Microsoft SQL Server and PostgreSQL integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations may require advanced JavaScript knowledge.
- Initial data synchronization can take time depending on the data volume.
- Handling very large binary data might require optimized configurations.