MongoDB managed connector tutorial

This tutorial explains how to set up automatic, ongoing syncs from a MongoDB database to a search-optimized index on Elastic Cloud. We’ll use an Atlas deployment, together with built-in sample datasets in this tutorial, but you can also use your own data.

This tutorial is an example of:

This tutorial has three main sections:

Follow the steps in the MongoDB documentation to create a free Atlas account:

In this example we’ll use the sample data available to MongoDB Atlas. You can do this in the MongoDB Atlas UI.

Use the Load Sample Dataset button in the Atlas UI, under Database Deployments. Find this by selecting the "…​" button next to your cluster name.

Figure 8. Loading sample data in Atlas UI

Detailed instructions are available in the Atlas documentation.

Once loaded, you can view your sample data in the Atlas UI, by selecting your database deployment’s Browse Collections button. Confirm that the sample databases have been added to your database deployment.

In this example, we’ll use the sample_mflix dataset, which contains data on movies and movie theaters. The database contains collections for certain metadata, including users and comments on specific movies. We’ll focus on the comments collection in this example. Each document contains a comment, and information such as the commenter’s name and email address.

Figure 9. A sample MongoDB document from the comments collection

Later, once the connector transforms MongoDB documents into Elasticsearch documents, you can compare their structure.

We’ve added data to our MongoDB Atlas cluster, and now we need to configure the Elastic MongoDB connector.

Before we switch over to working in Elastic Cloud, we need to gather some details about our MongoDB Atlas cluster. We’ll need these details to configure the Elastic MongoDB connector. You can find these details in the Atlas UI.

Find the following details:

Keep these details handy!

Everything is set up in MongoDB Atlas and we have the details we need to configure the Elastic MongoDB connector. First we’ll need to get an Elastic Cloud deployment up and running.

Log in to Elastic Cloud, and use the UI to create a deployment. You’ll need to run version 8.5.0+ or later.

Read prerequisites for Elastic managed connectors for full details.

Once you’re deployment is created, navigate to Search.

The Elastic connector will sync your MongoDB data into a search-optimized Elasticsearch index. The first step is to create your index in the Kibana UI.

In the main menu, navigate to Search > Content > Indices, or use the global search field.

Follow these steps to create your index:

Next we need to input our Atlas details to configure the connector.

Using the details gathered earlier, configure the MongoDB connector. Enter the details under the Configuration step.

Set the Direct connection option to false for this example. You must enable SSL/TLS for MongoDB Atlas, so toggle on the SSL/TLS Connection option.

Figure 10. Example configuration for the MongoDB connector

Once you’ve entered these details, select Save configuration.

Once you’ve configured your MongoDB connector, it’s time to schedule a sync.

The UI will take you to the Scheduling tab of your index overview page. We’ll schedule a recurring sync for this example, which will run every day at midnight.

In the Scheduling tab:

Once you save your sync schedule, the connector will start syncing your MongoDB Atlas data into Elasticsearch.

If all the configuration details are correct, the sync will begin and documents will start to appear in your Elasticsearch index.

As soon as your first documents are synced, you can view the documents and inspect the mapping for the index: