How to connect Microsoft SQL Server and PandaDoc
Create a New Scenario to Connect Microsoft SQL Server and PandaDoc
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 PandaDoc will be your first step. To do this, click "Choose an app," find Microsoft SQL Server or PandaDoc, 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 PandaDoc Node
Next, click the plus (+) icon on the Microsoft SQL Server node, select PandaDoc from the list of available apps, and choose the action you need from the list of nodes within PandaDoc.


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Authenticate PandaDoc
Now, click the PandaDoc node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your PandaDoc settings. Authentication allows you to use PandaDoc through Latenode.
Configure the Microsoft SQL Server and PandaDoc 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 PandaDoc 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Microsoft SQL Server, PandaDoc, 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 PandaDoc integration works as expected. Depending on your setup, data should flow between Microsoft SQL Server and PandaDoc (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 PandaDoc
PandaDoc + Microsoft SQL Server + Slack: When a document's status changes in PandaDoc, the document ID is logged into a Microsoft SQL Server database. Subsequently, a notification is sent to a designated Slack channel to inform the sales team.
PandaDoc + Zoho CRM + Microsoft SQL Server: Upon a PandaDoc document being completed, the corresponding deal stage in Zoho CRM is updated, and the contract details are logged in a Microsoft SQL Server database for record-keeping and analysis.
Microsoft SQL Server and PandaDoc 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 PandaDoc
Automate document workflows with PandaDoc in Latenode. Generate, send, and track proposals/contracts without manual steps. Use Latenode to trigger PandaDoc actions from your CRM or database. Parse data, pre-fill templates, and update records when documents are signed – saving time and ensuring data accuracy across systems. Scales easily.
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See how Latenode works
FAQ Microsoft SQL Server and PandaDoc
How can I connect my Microsoft SQL Server account to PandaDoc using Latenode?
To connect your Microsoft SQL Server account to PandaDoc 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 PandaDoc accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically generate contracts from SQL data?
Yes, you can! Latenode’s visual editor makes it easy. Automatically populate PandaDoc templates with data from Microsoft SQL Server for faster contract creation and approval.
What types of tasks can I perform by integrating Microsoft SQL Server with PandaDoc?
Integrating Microsoft SQL Server with PandaDoc allows you to perform various tasks, including:
- Automatically creating PandaDoc documents from new SQL Server entries.
- Updating SQL Server records when a PandaDoc document is completed.
- Tracking PandaDoc document status directly within SQL Server.
- Generating personalized proposals based on SQL Server customer data.
- Triggering document workflows based on changes in your SQL database.
What Microsoft SQL Server versions are supported on Latenode?
Latenode supports most Microsoft SQL Server versions, including Azure SQL Database, ensuring seamless integration regardless of your environment.
Are there any limitations to the Microsoft SQL Server and PandaDoc integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations might require custom JavaScript code.
- Large SQL Server queries may impact workflow execution time.
- PandaDoc API rate limits apply to high-volume document generation.