Microsoft SQL Server and MongoDB Integration

90% cheaper with Latenode

AI agent that builds your workflows for you

Hundreds of apps to connect

Replicate data from Microsoft SQL Server to MongoDB for scalable analytics and real-time dashboards. Latenode’s visual editor makes complex data transformations simple, while affordable execution-based pricing saves on high-volume transfers.

Swap Apps

Microsoft SQL Server

MongoDB

Step 1: Choose a Trigger

Step 2: Choose an Action

When this happens...

Name of node

action, for one, delete

Name of node

action, for one, delete

Name of node

action, for one, delete

Name of node

description of the trigger

Name of node

action, for one, delete

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Do this.

Name of node

action, for one, delete

Name of node

action, for one, delete

Name of node

action, for one, delete

Name of node

description of the trigger

Name of node

action, for one, delete

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Try it now

No credit card needed

Without restriction

How to connect Microsoft SQL Server and MongoDB

Create a New Scenario to Connect Microsoft SQL Server and MongoDB

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 MongoDB will be your first step. To do this, click "Choose an app," find Microsoft SQL Server or MongoDB, 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.

+
1

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.

+
1

Microsoft SQL Server

Node type

#1 Microsoft SQL Server

/

Name

Untitled

Connection *

Select

Map

Connect Microsoft SQL Server

Sign In

Run node once

Add the MongoDB Node

Next, click the plus (+) icon on the Microsoft SQL Server node, select MongoDB from the list of available apps, and choose the action you need from the list of nodes within MongoDB.

1

Microsoft SQL Server

+
2

MongoDB

Authenticate MongoDB

Now, click the MongoDB node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your MongoDB settings. Authentication allows you to use MongoDB through Latenode.

1

Microsoft SQL Server

+
2

MongoDB

Node type

#2 MongoDB

/

Name

Untitled

Connection *

Select

Map

Connect MongoDB

Sign In

Run node once

Configure the Microsoft SQL Server and MongoDB Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

1

Microsoft SQL Server

+
2

MongoDB

Node type

#2 MongoDB

/

Name

Untitled

Connection *

Select

Map

Connect MongoDB

MongoDB Oauth 2.0

#66e212yt846363de89f97d54
Change

Select an action *

Select

Map

The action ID

Run node once

Set Up the Microsoft SQL Server and MongoDB 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.
5

JavaScript

6

AI Anthropic Claude 3

+
7

MongoDB

1

Trigger on Webhook

2

Microsoft SQL Server

3

Iterator

+
4

Webhook response

Save and Activate the Scenario

After configuring Microsoft SQL Server, MongoDB, 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 MongoDB integration works as expected. Depending on your setup, data should flow between Microsoft SQL Server and MongoDB (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 MongoDB

Microsoft SQL Server + MongoDB + Slack: When a new or updated row is detected in Microsoft SQL Server, it triggers an update or insertion of a corresponding document in MongoDB. Upon successful data transfer, a notification is sent to a designated Slack channel, providing real-time monitoring of the data synchronization process.

Microsoft SQL Server + MongoDB + Google Sheets: Following the mirroring of data from Microsoft SQL Server to MongoDB, this automation tracks changes in MongoDB documents. Specifically, when a document is inserted or updated in MongoDB, relevant data is extracted and appended as a new row in a designated Google Sheet for analytical purposes.

Microsoft SQL Server and MongoDB 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.

About MongoDB

Use MongoDB in Latenode to automate data storage and retrieval. Aggregate data from multiple sources, then store it in MongoDB for analysis or reporting. Latenode lets you trigger workflows based on MongoDB changes, create real-time dashboards, and build custom integrations. Low-code tools and JavaScript nodes unlock flexibility for complex data tasks.

See how Latenode works

FAQ Microsoft SQL Server and MongoDB

How can I connect my Microsoft SQL Server account to MongoDB using Latenode?

To connect your Microsoft SQL Server account to MongoDB 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 MongoDB accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I synchronize product data between SQL Server and MongoDB?

Yes, you can! Latenode's flexible data mapping and transformation tools make synchronizing data seamless. Keep your product catalogs consistent across platforms effortlessly.

What types of tasks can I perform by integrating Microsoft SQL Server with MongoDB?

Integrating Microsoft SQL Server with MongoDB allows you to perform various tasks, including:

  • Migrating data from SQL Server to MongoDB for improved scalability.
  • Creating real-time data pipelines between SQL Server and MongoDB.
  • Backing up SQL Server data to MongoDB for disaster recovery.
  • Analyzing SQL Server data using MongoDB's aggregation framework.
  • Enriching MongoDB data with relational data from SQL Server.

What authentication methods does Latenode support for Microsoft SQL Server?

Latenode supports SQL Server authentication, Windows authentication, and Azure Active Directory for secure access to your data.

Are there any limitations to the Microsoft SQL Server and MongoDB integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Complex data transformations might require JavaScript code.
  • Initial data synchronization can be time-consuming for large datasets.
  • Real-time synchronization depends on network latency.

Try now