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


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Authenticate Google Sheets
Now, click the Google Sheets node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Sheets settings. Authentication allows you to use Google Sheets through Latenode.
Configure the Microsoft SQL Server and Google Sheets 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 Google Sheets 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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Save and Activate the Scenario
After configuring Microsoft SQL Server, Google Sheets, 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 Google Sheets integration works as expected. Depending on your setup, data should flow between Microsoft SQL Server and Google Sheets (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 Google Sheets
Microsoft SQL Server + Google Sheets + Slack: When a row is updated in Microsoft SQL Server, the changes are reflected in Google Sheets. A notification is then sent to a Slack channel to inform the team about the critical stock level update.
Microsoft SQL Server + Google Sheets + Tableau: Data is extracted from SQL Server using a query and then added to a Google Sheet. Tableau is then manually updated to reflect the changes made in Google Sheets, providing updated dashboards.
Microsoft SQL Server and Google Sheets 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 Google Sheets
Use Google Sheets in Latenode to automate data entry, reporting, and analysis. Read/write data to spreadsheets as part of larger workflows triggered by events or schedules. Avoid manual updates by linking Sheets to other apps. Integrate data from any source via API and transform it into actionable insights.
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FAQ Microsoft SQL Server and Google Sheets
How can I connect my Microsoft SQL Server account to Google Sheets using Latenode?
To connect your Microsoft SQL Server account to Google Sheets 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 Google Sheets accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically back up SQL data to Google Sheets?
Yes, you can easily automate SQL data backups to Google Sheets. Latenode's visual editor simplifies workflow creation, ensuring secure and reliable data replication without complex coding.
What types of tasks can I perform by integrating Microsoft SQL Server with Google Sheets?
Integrating Microsoft SQL Server with Google Sheets allows you to perform various tasks, including:
- Creating reports in Google Sheets based on SQL Server data.
- Automatically updating spreadsheets with real-time database changes.
- Generating charts from SQL Server data in Google Sheets.
- Importing Google Sheets data into SQL Server tables.
- Sending email alerts from SQL Server based on data in Google Sheets.
HowsecureistheMicrosoftSQLServerintegrationonLatenode?
Latenode uses secure authentication and encryption methods to protect your data during Microsoft SQL Server and Google Sheets integrations. Your credentials are never exposed.
Are there any limitations to the Microsoft SQL Server and Google Sheets integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers may be subject to API rate limits.
- Complex SQL queries may require optimization for optimal performance.
- Custom JavaScript code requires testing for error handling.