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


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Authenticate Nimble
Now, click the Nimble node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Nimble settings. Authentication allows you to use Nimble through Latenode.
Configure the Microsoft SQL Server and Nimble 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 Nimble 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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Nimble
Trigger on Webhook
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Microsoft SQL Server
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Webhook response


Save and Activate the Scenario
After configuring Microsoft SQL Server, Nimble, 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 Nimble integration works as expected. Depending on your setup, data should flow between Microsoft SQL Server and Nimble (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 Nimble
Microsoft SQL Server + Nimble + Slack: When a new or updated row is detected in Microsoft SQL Server, a contact is created or updated in Nimble. Subsequently, a message is sent to a designated Slack channel to notify the team about the new or updated client information.
Nimble + Microsoft SQL Server + Google Sheets: When a contact is created or updated in Nimble, customer data is retrieved from Microsoft SQL Server using a query. This data is then used to update a row in Google Sheets.
Microsoft SQL Server and Nimble 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 Nimble
Use Nimble within Latenode to enrich contact data and automate outreach. Update your CRM, personalize emails, and trigger follow-ups based on engagement—all visually. Latenode handles the workflow logic and scale, while Nimble provides targeted contact intelligence for smarter automation.
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See how Latenode works
FAQ Microsoft SQL Server and Nimble
How can I connect my Microsoft SQL Server account to Nimble using Latenode?
To connect your Microsoft SQL Server account to Nimble 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 Nimble accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I sync new SQL leads to Nimble?
Yes, you can! Latenode's visual editor makes it easy to sync new Microsoft SQL Server leads to Nimble, ensuring your sales team always has the latest contact information.
What types of tasks can I perform by integrating Microsoft SQL Server with Nimble?
Integrating Microsoft SQL Server with Nimble allows you to perform various tasks, including:
- Create new Nimble contacts from Microsoft SQL Server database entries.
- Update Nimble contact details with information from Microsoft SQL Server.
- Trigger email campaigns in Nimble based on Microsoft SQL Server data changes.
- Synchronize activity history between Microsoft SQL Server and Nimble.
- Generate reports in Nimble using data from Microsoft SQL Server.
How secure is Microsoft SQL Server data access on Latenode?
Latenode employs encryption and secure data handling practices, safeguarding your Microsoft SQL Server data during integration and automation processes.
Are there any limitations to the Microsoft SQL Server and Nimble integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers from Microsoft SQL Server may impact workflow execution time.
- Complex SQL queries might require optimization for efficient data retrieval.
- Custom field mappings in Nimble may need manual configuration.