Elastic MongoDB connector reference

The Elastic MongoDB connector is a connector for MongoDB data sources. This connector is written in Python using the Elastic connector framework.

View the source code for this connector (branch main, compatible with Elastic 9.0).

This connector is also available as a self-managed connector from the Elastic connector framework. To use this connector as a self-managed connector, satisfy all self-managed connector requirements.

This connector is compatible with MongoDB Atlas and MongoDB 3.6 and later.

The data source and your Elastic deployment must be able to communicate with each other over a network.

The following configuration fields are required to set up the connector:

host

The URI of the MongoDB host. Examples:

• mongodb+srv://my_username:my_password@cluster0.mongodb.net/mydb?w=majority
• mongodb://127.0.0.1:27017

user

The MongoDB username the connector will use.

The user must have access to the configured database and collection. You may want to create a dedicated, read-only user for each connector.

password

The MongoDB password the connector will use.

database

The MongoDB database to sync. The database must be accessible using the configured username and password.

collection

The MongoDB collection to sync. The collection must exist within the configured database. The collection must be accessible using the configured username and password.

direct_connection

Whether to use the direct connection option for the MongoDB client. Default value is False.

ssl_enabled

Whether to establish a secure connection to the MongoDB server using SSL/TLS encryption. Ensure that your MongoDB deployment supports SSL/TLS connections. Enable if your MongoDB cluster uses DNS SRV records (namely MongoDB Atlas users).

Default value is False.

ssl_ca

Specifies the root certificate from the Certificate Authority. The value of the certificate is used to validate the certificate presented by the MongoDB instance.

tls_insecure

Skips various certificate validations (if SSL is enabled). Default value is False.

To create a new MongoDB connector:

1. In the Kibana UI, navigate to the Search → Content → Connectors page from the main menu, or use the global search field.
2. Follow the instructions to create a new MongoDB self-managed connector.

You can use the Elasticsearch Create connector API to create a new self-managed MongoDB self-managed connector.

For example:

 PUT _connector/my-mongodb-connector {
  "index_name": "my-elasticsearch-index",
  "name": "Content synced from MongoDB",
  "service_type": "mongodb"
}

Refer to the Elasticsearch API documentation for details of all available Connector APIs.

To use this connector as a self-managed connector, see Self-managed connectors For additional usage operations, see Connectors UI in Kibana.

• A bug introduced in 8.12.0 causes the connector to fail to sync Mongo Atlas urls (mongo+srv) unless SSL/TLS is enabled.

It’s not possible to use expressions like new Date() inside an aggregation pipeline. These expressions won’t be evaluated by the underlying MongoDB client, but will be passed as a string to the MongoDB instance. A possible workaround is to use aggregation variables.

Incorrect (new Date() will be interpreted as string):

{
    "aggregate": {
        "pipeline": [
            {
                "$match": {
                  "expiresAt": {
                    "$gte": "new Date()"
                  }
                }
            }
        ]
    }
}

Correct (usage of $$NOW):

{
  "aggregate": {
    "pipeline": [
      {
        "$addFields": {
          "current_date": {
            "$toDate": "$$NOW"
          }
        }
      },
      {
        "$match": {
          "$expr": {
            "$gte": [
              "$expiresAt",
              "$current_date"
            ]
          }
        }
      }
    ]
  }
}

Currently, the MongoDB connector does not support working with self-signed or custom CA certs when connecting to your self-managed MongoDB host.

This can be worked around in development environments, by appending certain query parameters to the configured host.

For example, if your host is mongodb+srv://my.mongo.host.com, appending ?tls=true&tlsAllowInvalidCertificates=true will allow disabling TLS certificate verification.

The full host in this example will look like this:

mongodb+srv://my.mongo.host.com/?tls=true&tlsAllowInvalidCertificates=true

A bug introduced in 8.12.0 causes the Connectors docker image to error out if run using MongoDB as its source. The command line will output the error cannot import name 'coroutine' from 'asyncio'. *** This issue is fixed in versions 8.12.2* and 8.13.0. ** This bug does not affect Elastic managed connectors.

See Known issues for any issues affecting all connectors.

See Troubleshooting.

See Security.

You can deploy the MongoDB connector as a self-managed connector using Docker. Follow these instructions.

curl https://raw.githubusercontent.com/elastic/connectors/main/config.yml.example --output ~/connectors-config/config.yml

# When connecting to your cloud deployment you should edit the host value
elasticsearch.host: http://host.docker.internal:9200
elasticsearch.api_key: <ELASTICSEARCH_API_KEY>

connectors:
  -
    connector_id: <CONNECTOR_ID_FROM_KIBANA>
    service_type: mongodb
    api_key: <CONNECTOR_API_KEY_FROM_KIBANA>1

docker run \
-v ~/connectors-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/integrations/elastic-connectors:9.0.0-beta1.0 \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to DOCKER.md in the elastic/connectors repo for more details.

Find all available Docker images in the official registry.

The following describes the default syncing behavior for this connector. Use sync rules and ingest pipelines to customize syncing for specific indices.

All documents in the configured MongoDB database and collection are extracted and transformed into documents in your Elasticsearch index.

• The connector creates one Elasticsearch document for each MongoDB document in the configured database and collection.
• For each document, the connector transforms each MongoDB field into an Elasticsearch field.
• For each field, Elasticsearch dynamically determines the data type^.

This results in Elasticsearch documents that closely match the original MongoDB documents.

The Elasticsearch mapping is created when the first document is created.

Each sync is a "full" sync. For each MongoDB document discovered:

• If it does not exist, the document is created in Elasticsearch.
• If it already exists in Elasticsearch, the Elasticsearch document is replaced and the version is incremented.
• If an existing Elasticsearch document no longer exists in the MongoDB collection, it is deleted from Elasticsearch.
• Embedded documents are stored as an object field in the parent document.

This is recursive, because embedded documents can themselves contain embedded documents.

The following sections describe Sync rules for this connector.

Basic sync rules are identical for all connectors and are available by default.

Advanced rules for MongoDB can be used to express either find queries or aggregation pipelines. They can also be used to tune options available when issuing these queries/pipelines.

For find queries, the structure of this JSON DSL should look like:

{
	"find":{
		"filter": {
			// find query goes here
		},
		"options":{
			// query options go here
		}
	}
}

For example:

{
	"find": {
		"filter": {
			"$text": {
				"$search": "garden",
				"$caseSensitive": false
			}
		},
		"skip": 10,
		"limit": 1000
	}
}

find queries also support additional options, for example the projection object:

{
  "find": {
    "filter": {
      "languages": [
        "English"
      ],
      "runtime": {
        "$gt":90
      }
    },
    "projection":{
      "tomatoes": 1
    }
  }
}

Where the available options are:

• allow_disk_use (true, false) — When set to true, the server can write temporary data to disk while executing the find operation. This option is only available on MongoDB server versions 4.4 and newer.
• allow_partial_results (true, false) — Allows the query to get partial results if some shards are down.
• batch_size (Integer) — The number of documents returned in each batch of results from MongoDB.
• filter (Object) — The filter criteria for the query.
• limit (Integer) — The max number of docs to return from the query.
• max_time_ms (Integer) — The maximum amount of time to allow the query to run, in milliseconds.
• no_cursor_timeout (true, false) — The server normally times out idle cursors after an inactivity period (10 minutes) to prevent excess memory use. Set this option to prevent that.
• projection (Array, Object) — The fields to include or exclude from each doc in the result set. If an array, it should have at least one item.
• return_key (true, false) — Return index keys rather than the documents.
• show_record_id (true, false) — Return the $recordId for each doc in the result set.
• skip (Integer) — The number of docs to skip before returning results.

Similarly, for aggregation pipelines, the structure of the JSON DSL should look like:

{
	"aggregate":{
		"pipeline": [
			// pipeline elements go here
		],
		"options": {
            // pipeline options go here
		}
    }
}

Where the available options are:

• allowDiskUse (true, false) — Set to true if disk usage is allowed during the aggregation.
• batchSize (Integer) — The number of documents to return per batch.
• bypassDocumentValidation (true, false) — Whether or not to skip document level validation.
• collation (Object) — The collation to use.
• comment (String) — A user-provided comment to attach to this command.
• hint (String) — The index to use for the aggregation.
• let (Object) — Mapping of variables to use in the pipeline. See the server documentation for details.
• maxTimeMs (Integer) — The maximum amount of time in milliseconds to allow the aggregation to run.

As part of the 8.8.0 release the MongoDB connector was moved from the Ruby connectors framework to the Elastic connector framework.

This change introduces minor formatting modifications to data ingested from MongoDB:

1. Nested object id field name has changed from "_id" to "id". For example, if you had a field "customer._id", this will now be named "customer.id".
2. Date format has changed from YYYY-MM-DD'T'HH:mm:ss.fff'Z' to YYYY-MM-DD'T'HH:mm:ss

If your MongoDB connector stopped working after migrating from 8.7.x to 8.8.x, read the workaround outlined in Known issues. If that does not work, we recommend deleting the search index attached to this connector and re-creating a MongoDB connector from scratch.