Get Started with the MongoDB Atlas Source Connector for Confluent Cloud

The fully-managed MongoDB Atlas Source connector for Confluent Cloud moves data from a MongoDB replica set into an Apache Kafka® cluster. The connector configures and consumes change stream event documents and publishes them to a Kafka topic.

Note

Sign up for a Confluent Cloud trial and get $400 of free credit.
If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.

Features

The MongoDB Atlas Source connector supports both MongoDB Atlas and self-managed MongoDB databases.

The connector offers the following features:

At least once delivery: The connector guarantees that records are delivered at least once to the Kafka topic.
Topics created automatically: The connector automatically creates Kafka topics using the naming convention: <prefix>.<database-name>.<collection-name>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3. You add the prefix when setting up the connection in the Quick Start steps. For more information, see Maximum message size. Note that if you want to create topics with specific settings, create the topics before running this connector.
Database authentication: The connector supports both username/password-based and X.509 certificate-based authentication. For more information on MONGODB-X.509-based authentication setup, see connector authentication.
Output data formats: The connector supports Avro, Byte, JSON (schemaless), JSON Schema, Protobuf or String output data. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
Large size records: The connector supports MongoDb documents up to 20 MB in size on Dedicated Kafka clusters and 8 MB on other clusters.
Select configuration properties:
- poll.await.time.ms: The amount of time to wait before checking for new results in the change stream.
- poll.max.batch.size: The maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.
Offset management capabilities: The connector supports offset management. For more information, see Manage custom offsets.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Limitations

Be sure to review the following information.

For connector limitations, see MongoDB Atlas Source Connector limitations.
If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.

Maximum message size

This connector creates topics automatically. When it creates topics, the internal connector configuration property max.message.bytes is set to the following:

Basic cluster: 8 MB
Standard cluster: 8 MB
Enterprise cluster: 8 MB
Dedicated cluster: 20 MB

For more information about Confluent Cloud clusters, see Kafka Cluster Types in Confluent Cloud.

Manage custom offsets

You can manage the offsets for this connector. Offsets provide information on the point in the system from which the connector is accessing data. For more information, see Manage Offsets for Fully-Managed Connectors in Confluent Cloud.

To manage offsets:

Manage offsets using Confluent Cloud APIs. For more information, see Cluster API reference.

Get the current offset

To get the current offset, make a GET request that specifies the environment, Kafka cluster, and connector name.

GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets
Host: https://api.confluent.cloud

Response:

Successful calls return HTTP 200 with a JSON payload that describes the offset.

{
    "id": "lcc-example123",
    "name": "{connector_name}",
    "offsets": [
        {
            "partition": {
                "ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
            },
            "offset": {
                "_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A1004737030_TRUNCATED\"}"
            }
        }
    ],
    "metadata": {
        "observed_at": "2024-03-28T17:57:48.139635200Z"
    }
}

Responses include the following information:

The position of latest offset.
The observed time of the offset in the metadata portion of the payload. The observed_at time indicates a snapshot in time for when the API retrieved the offset. A running connector is always updating its offsets. Use observed_at to get a sense for the gap between real time and the time at which the request was made. By default, offsets are observed every minute. Calling GET repeatedly will fetch more recently observed offsets.
Information about the connector.

Update the offset

To update the offset, make a POST request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies new offset and a patch type.

POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
Host: https://api.confluent.cloud

 {
     "type": "PATCH",
     "offsets": [
       {
           "partition": {
               "ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
           },
           "offset": {
               "_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A100473703049_TRUNCATED\"}"
           }
       }
   ]
 }

Considerations:

You can only make one offset change at a time for a given connector.
This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.
For source connectors, the connector attempts to read from the position defined by the requested offsets.

Response:

Successful calls return HTTP 202 Accepted with a JSON payload that describes the offset.

{
    "id": "lcc-example123",
    "name": "{connector_name}",
    "offsets": [
        {
            "partition": {
                "ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
            },
            "offset": {
                "_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A1004737030_TRUNCATED\"}"
            }
        }
    ],
    "requested_at": "2024-03-28T17:58:45.606796307Z",
    "type": "PATCH"
}

Responses include the following information:

The requested position of the offsets in the source.
The time of the request to update the offset.
Information about the connector.

Delete the offset

To delete the offset, make a POST request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies the delete type.

 POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
 Host: https://api.confluent.cloud

{
  "type": "DELETE"
}

Considerations:

Delete requests delete the offset for the provided partition and reset to the base state. A delete request is as if you created a fresh new connector.
This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.
Do not issue delete and patch requests at the same time.
For source connectors, the connector attempts to read from the position defined in the base state.

Response:

Successful calls return HTTP 202 Accepted with a JSON payload that describes the result.

{
  "id": "lcc-example123",
  "name": "{connector_name}",
  "offsets": [],
  "requested_at": "2024-03-28T17:59:45.606796307Z",
  "type": "DELETE"
}

Responses include the following information:

Empty offsets.
The time of the request to delete the offset.
Information about the Kafka cluster and connector.
The type of request.

Get the status of an offset request

To get the status of a previous offset request, make a GET request that specifies the environment, Kafka cluster, and connector name.

GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request/status
Host: https://api.confluent.cloud

Considerations:

The status endpoint always shows the status of the most recent PATCH/DELETE operation.

Response:

Successful calls return HTTP 200 with a JSON payload that describes the result. The following is an example of an applied patch.

{
   "request": {
      "id": "lcc-example123",
      "name": "{connector_name}",
      "offsets": [
          {
              "partition": {
                  "ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
              },
              "offset": {
                  "_id": "{\"_data\": \"82661F7DDE000000012B042C0100296E5A100473703_TRUNCATED\"}"
              }
          }
      ],
      "requested_at": "2024-03-28T17:58:45.606796307Z",
      "type": "PATCH"
   },
   "status": {
      "phase": "APPLIED",
      "message": "The Connect framework-managed offsets for this connector have been altered successfully. However, if this connector manages offsets externally, they will need to be manually altered in the system that the connector uses."
   },
   "previous_offsets": [
       {
           "partition": {
               "ns": "mongodb+srv://cluster0.2a5tnof.mongodb.net/"
           },
           "offset": {
               "_id": "{\"_data\": \"82661FF4CF000000042B042C0100296E5A100473703049_TRUNCATED\"}"
           }
       }
   ],
   "applied_at": "2024-03-28T17:58:48.079141883Z"
}

Responses include the following information:

The original request, including the time it was made.
The status of the request: applied, pending, or failed.
The time you issued the status request.
The previous offsets. These are the offsets that the connector last updated prior to updating the offsets. Use these to try to restore the state of your connector if a patch update causes your connector to fail or to return a connector to its previous state after rolling back.

JSON payload

The table below offers a description of the unique fields in the JSON payload for managing offsets of the MongoDB Atlas Source connector.

Field	Definition	Required/Optional
`ns`	`ns` is the connection string, including the connection host. If the configuration file for the connector includes a value in `offset.partition.name`, the value in `offset.partition.name` is used for `ns`.	Required
`_id`	`_id` is the `_data` field from the source record in MongoDB.	Required

Quick Start

Use this quick start to get up and running with the Confluent Cloud MongoDB Atlas Source connector. The quick start provides the basics of selecting the connector and configuring it to consume data from MongoDB and persist the data to Kafka.

Prerequisites

Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.
Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
Access to a MongoDB database. Note that the connection user must have privileged action “find” to query the MongoDB database. For more information, see Query and Write Actions.
The MongoDB hostname address must provide a service record (SRV) when connecting to MONGODB_ATLAS. For MONGODB_SELF_MANAGED, a standard connection string is required.
The connector automatically creates Kafka topics using the naming convention: <prefix>.<database-name>.<collection-name>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3. If you want to create topics with specific settings, create the topics before running this connector.
Important

If you are configuring granular access using a service account, and you leave the optional Topic prefix (prefix) configuration property empty, the connector uses the Database name (database-name) entered as the prefix. You must grant ACL CREATE and WRITE access to the database name prefix (see ACL access). If both the prefix and database-name configuration properties are not used, you must do one of the following:
- If you know the databases to capture, create individual ACLs for each topic. The topic name will have the database name as the prefix.
- Create ACLs for all Kafka topics, using the (*) wildcard in the ACL entries as shown below:
  confluent kafka acl create --allow --service-account "<service-account-id>" --operation create --topic "*" .. code-block:: bash confluent kafka acl create --allow --service-account "<service-account-id>" --operation write --topic "*"
- Create create RBAC role bindings.
If you have a VPC-peered cluster in Confluent Cloud, consider configuring a PrivateLink Connection between MongoDB Atlas and the VPC. For additional networking considerations, see Networking and DNS. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.

Kafka cluster credentials. The following lists the different ways you can provide credentials.
- Enter an existing service account resource ID.
- Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.
- Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster

To create and launch a Kafka cluster in Confluent Cloud, see Create a kafka cluster in Confluent Cloud.

Step 2: Add a connector

In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector

Click the MongoDB Atlas Source connector card.

Step 4: Enter the connector details

Note

Make sure you have all your prerequisites completed.
An asterisk ( * ) designates a required entry.
You can specify connection string options in the connection host. For example: cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local. For more information about connection string options, see MongoDB Connection String Options.

Note

The connector does not support following connection string options in connection.host config: tlsCertificateKeyFile, tlsCertificateKeyFilePassword, tlsCAFile, tlsAllowInvalidCertificates, tlsInsecure, tlsAllowInvalidHostnames, authMechanism, authMechanismProperties, gssapiServiceName.
Other options like readPreference, readConcernLevel, or w defined in MongoDB Connection String Options can be configured in connection.host configuration. For example, cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local&appName=test&w=majority.
The connector supports connecting to self-managed MongoDB database.
Use mongodb.instance.type as MONGODB_SELF_MANAGED and specify the connection.host accordingly to connect to self-managed instance. For example, 54.190.171.123:27017/?authSource=admin.

At the MongoDB Atlas Source Connector screen, complete the following:

Define a topic prefix

In the Topic prefix field, define a topic prefix your connector will use to publish to Kafka topics. The connector will Kafka topics using the following naming convention: <prefix>.<database-name>.<collection-name>. If you want to create topics with specific settings, create the topics before running this connector.

Important

If you are configuring granular access using a service account, and you leave the optional Topic prefix (prefix) configuration property empty, the connector uses the Database name (database-name) entered as the prefix. You must grant ACL CREATE and WRITE access to the database name prefix (see ACL access). If both the prefix and database-name configuration properties are not used, you must do one of the following:

If you know the databases to capture, create individual ACLs for each topic. The topic name will have the database name as the prefix.

Create ACLs for all Kafka topics, using the (*) wildcard in the ACL entries as shown below:

  confluent kafka acl create --allow --service-account
  "<service-account-id>" --operation create --topic "*"

.. code-block:: bash

  confluent kafka acl create --allow --service-account
  "<service-account-id>" --operation write --topic "*"

Create create RBAC role bindings.

Kafka credentials

Select the way you want to provide Kafka Cluster credentials. You can choose one of the following options:
- My account: This setting allows your connector to globally access everything that you have access to. With a user account, the connector uses an API key and secret to access the Kafka cluster. This option is not recommended for production.
- Service account: This setting limits the access for your connector by using a service account. This option is recommended for production.
- Use an existing API key: This setting allows you to specify an API key and a secret pair. You can use an existing pair or create a new one. This method is not recommended for production environments.
Note

Freight clusters support only service accounts for Kafka authentication.

Click Continue.

Authentication

Add the following MongoDB connection details:

Under MongoDB instance type, specify the MongoDB deployment type. Use MONGODB_ATLAS for cloud hosted Atlas clusters or MONGODB_SELF_MANAGED for self hosted MongoDB instances.
Under MongoDB authentication mechanism, choose an authentication mechanism for MongoDB:
- Use SCRAM-SHA-256 for username/password authentication.
- Use MONGODB-X509 for certificate-based authentication. For MONGODB-X509, you must configure the SSL keystore properties.
Under MongoDB credentials, enter the following MongoDB Atlas credentials:
- Connection host: The MongoDB host with connection string options. Use a hostname address and not a full URL. For example, use cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary for MONGODB_ATLAS and 54.190.171.123:27017/?authSource=admin for MONGODB_SELF_MANAGED.
  
  Note
  
  You don’t need to manually add the connection string parameters authMechanism=MONGODB-X509&authSource=$external as part of the host. The connector automatically includes the parameter when you select MONGODB-X.509 as the authentication mechanism.
- Connection user: The MongoDB Atlas connection user.
- Connection password: The MongoDB Atlas connection password. When entering the password, make sure that any special characters are URL encoded.
Under MongoDB Atlas Database Details, enter the following MongoDB Atlas database details:
- Database name: The MongoDB Atlas database name. If not set, all databases in the cluster are watched.
- Collection name: Single MongoDB collection to watch. If not set, all collections databases in the cluster are watched.
Under SSL Configuration, configure the following properties:
- Upload the SSL keystore file containing the server certificate and enter the SSL keystore password used to access the keystore.
- Upload the SSL truststore file containing a server CA certificate and enter the truststore SSL truststore password used to access the truststore.
Click Continue.

Configuration

Configure the following:
- Select the output record value format (data going to the Kafka topic): AVRO, BSON, JSON, JSON_SR (JSON Schema), PROTOBUF, or STRING. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). For additional information, see Schema Registry Enabled Environments.
  
  If you select AVRO, be sure to set Compatibility mode (schema.compatibility.level) to NONE in Schema Registry. Note that schemas are generated per document in isolation. If not set to NONE, there is a chance that the new schema generated for the new document will not be backward compatible with previous versions of the schema.
Show advanced configurations
- Schema context: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the Default context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a Source connector uses only that schema context to register a schema and a Sink connector uses only that schema context to read from. For more information about setting up a schema context, see What are schema contexts and when should you use them?.
- JSON output decimal format: Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals: BASE64 to serialize DECIMAL logical types as base64 encoded binary data and NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.
- Topic namespace map: Add a JSON object that maps change stream document namespaces to topics. For additional information, see Topic Namespace Map. Multiple collections with records having varying schema are mapped to a single topic for AVRO, JSON_SR, or PROTOBUF data formats. These are registered to a single subject name. If the schemas are not backward compatible, the connector fails until you change the schema compatibility in Confluent Cloud Schema Registry.
- Publish full document only: Set whether to return only the fullDocument field from the change stream event document produced by any update event. The fullDocument field contains the most current version of the updated document. Sets the change.stream.full.document=updateLookup setting so updated documents will be included.
- Publish tombstone events on document deletion: When set to true, the connector returns the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when publish.full.document.only is true.
- Change stream full document: Determines what to return for update operations when using a Change Stream. The default setting returns the differences between the original document and the updated document. The updateLookup setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The whenAvailable setting returns the updated document, if available. The required setting returns the updated document and raises an error if it is not available.
- Change stream full document before change: Configures the document pre-image your change stream returns on update operations. The default setting suppresses the document pre-image. When set to whenAvailable setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. The required setting returns the document pre-image and raises an error if it is not available.
- Output JSON formatter: Sets the output format of JSON strings. The format can be either, DefaultJson, ExtendedJson, or SimplifiedJson.
- Topic separator: A separator to use when the connector joins prefix, database, collection, and suffix values. These joined values create the Kafka topic name where data is published. Defaults to ..
- Topic suffix: A suffix to append to database and collection names to generate the name of the Kafka topic the connector creates.
- Value Subject Name Strategy: Determines how to construct the subject name under which the value schema is registered with Schema Registry. This property defaults to TopicNameStrategy. Set this property to RecordNameStrategy to derive the subject name from the record name. For more information, see Subject name strategy.
- Output schema infer value: Whether the connector should infer the schema of the SourceRecord. The connector processes each document in isolation and may generate many schemas. This setting only works with AVRO, JSON, JSON_SR, or PROTOBUF data formats.
Auto-restart policy
- Enable Connector Auto-restart: Control the auto-restart behavior of the connector and its task in the event of user-actionable errors. Defaults to true, enabling the connector to automatically restart in case of user-actionable errors. Set this property to false to disable auto-restart for failed connectors. In such cases, you would need to manually restart the connector.
- Poll wait time (ms): The amount of time to wait before checking for new results on the change stream.
- Maximum documents to include in a batch: The maximum number of change stream documents to include in a single batch when polling for new data.
- Pipeline: An array of JSON objects describing the pipeline operations to filter or modify the change events output.
- Startup mode: Specifies how the connector starts up when there is no source offset available. If no source offset is available, the connector may either ignore all or some of the existing source data, or it may first copy all existing source data and then continue processing new data. When set to latest (the default), the connector ignores all existing source data. If set to timestamp, the connector actuates startup.mode.timestamp.* properties. If no properties are configured, timestamp is equivalent to latest. If set to copy_existing, the connector copies all existing source data to Change Stream events. This setting is equivalent to the deprecated setting copy.existing=true.
- Start timestamp: Actuated only if startup.mode=timestamp. Specifies the starting point for the change stream. Accepted values can be an integer number of seconds since the Epoch in decimal format (for example, 30), or an instant in the ISO-8601 format with one second precision (for example, 1970-01-01T00:00:30Z), or a BSON Timestamp in the canonical extended JSON (v2) format (for example, {"$timestamp": {"t": 30, "i": 0}}).
- Copy existing namespace regex: Regular expression that matches the namespaces (databaseName.collectionName) from which to copy data.
- Copy existing pipeline: An array of JSON objects describing the pipeline operations to run when copying existing data. It will only be applied for existing documents which are being copied.
- Cursor batch size: The number of documents to return in a batch. The value defaults to 0. The maximum cursor batch size is 50.
- Heartbeat interval: The number of milliseconds the connector waits between sending heartbeat messages.
- Heartbeat topic name: The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the heartbeat.interval.ms setting to enable this feature.
- Offset partition name: The custom offset partition name to use. Use this option to instruct the connector to start a new change stream when an existing offset contains an invalid resume token. If you leave this setting blank, the connector uses the default partition name from the connection details.
- Error tolerance: Allows you to customize how the connector handles errors. By default, this is set to NONE and the connector handles errors using the error handling tolerance configured for the Connect framework.
- Output errors: Whether or not the connector sends output conversion errors to the dead letter queue (DLQ). When using a schema, this prevents unprocessable (poison) messages from causing the connector task to fail. The connector outputs messages to the DLQ as extended JSON for the specified topic. Enabling this property requires that the Error tolerance property be set to all. By default, the connector does not output messages to the DLQ.
- Server API version: The MongoDB server API version to use. This property is disabled by default.
- Deprecation errors: Whether or not to require the connector to report the use of deprecated server APIs as errors. This property is disabled by default.
- Server API: Whether or not to require strict server API version enforcement. This property is disabled by default.
Transforms
- Single Message Transforms: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.
For all property values and definitions, see Configuration Properties.
Click Continue.

Sizing

The connector supports running a single task.

Click Continue.

Review and Launch

Verify the connection details by previewing the running configuration.

Tip

For information about previewing your connector output, see Data Previews for Confluent Cloud Connectors.
After you’ve validated that the properties are configured to your satisfaction, click Launch.

The status for the connector should go from Provisioning to Running.

Step 5: Check the Kafka topic

After the connector is running, verify that MongoDB documents are populating the Kafka topic. If the config startup.mode=copy_existing and the connector restarts due to any reason, you may see duplicate records in the topic.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Using the Confluent CLI

Complete the following steps to set up and run the connector using the Confluent CLI.

Note

Make sure you have all your prerequisites completed.

Step 1: List the available connectors

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: List the connector configuration properties

Enter the following command to show the connector configuration properties:

confluent connect plugin describe <connector-plugin-name>

The command output shows the required and optional configuration properties.

Step 3: Create the connector configuration file

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.

 {
     "connector.class": "MongoDbAtlasSource",
     "name": "<my-connector-name>",
     "kafka.auth.mode": "KAFKA_API_KEY",
     "kafka.api.key": "<my-kafka-api-key>",
     "kafka.api.secret": "<my-kafka-api-secret>",
     "topic.prefix": "<topic-prefix>",
     "connection.host": "<database-host-address>",
     "connection.user": "<database-username>",
     "connection.password": "<database-password>",
     "database": "<database-name>",
     "collection": "<database-collection-name>",
     "poll.await.time.ms": "5000",
     "poll.max.batch.size": "1000",
     "startup.mode": "copy_existing",
     "output.data.format": "JSON"
     "tasks.max": "1"
}

Note the following property definitions:

"connector.class": Identifies the connector plugin name.
"name": Sets a name for your new connector.

"kafka.auth.mode": Identifies the connector authentication mode you want to use. There are two options: SERVICE_ACCOUNT or KAFKA_API_KEY (the default). To use an API key and secret, specify the configuration properties kafka.api.key and kafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the property kafka.service.account.id=<service-account-resource-ID>. To list the available service account resource IDs, use the following command:
```
confluent iam service-account list
```
For example:
```
confluent iam service-account list

   Id     | Resource ID |       Name        |    Description
+---------+-------------+-------------------+-------------------
   123456 | sa-l1r23m   | sa-1              | Service account 1
   789101 | sa-l4d56p   | sa-2              | Service account 2
```

(Optional) "topic.prefix": Enter a topic prefix. The connector automatically creates Kafka topics using the naming convention: <prefix>.<database-name>.<collection-name>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3. If you want to create topics with specific settings, create the topics before running this connector. Note the following:
- If you are configuring granular access using a service account, you must set up ACLs for the topic prefix.
- If you are using a dedicated cluster and have a MongoDb document greater than 2MB in size, create the topic beforehand with property max.message.bytes set to match the largest document size or greater than the largest document size (8388608 bytes maximum).
Important

If you are configuring granular access using a service account, and you leave the optional Topic prefix (topic.prefix) configuration property empty, you must grant ACL CREATE and WRITE access to all the Kafka topics or create RBAC role bindings. To add ACLs, you use the (*) wildcard in the ACL entries as shown in the following examples.
```
confluent kafka acl create --allow --service-account
"<service-account-id>" --operation create --topic "*"
```
```
confluent kafka acl create --allow --service-account
"<service-account-id>" --operation write --topic "*"
```
(Optional) "topic.namespace.map": A JSON map that maps change stream document namespaces to topics. For example: {\"db\": \"dbTopic\", \"db.coll\": \"dbCollTopic\"} will map all change stream documents from the db database to dbTopic.<collectionName> apart from any documents from the db.coll namespace which map to the dbCollTopic topic. If you want to map all messages to a single topic use *. For example: {\"*\": \"everyThingTopic\", \"db.coll\": \"exceptionToTheRuleTopic\"} will map all change stream documents to the everyThingTopic apart from the db.coll messages. Note that any prefix configuration will still apply. If multiple collections with records having varying schema are mapped to a single topic with AVRO, JSON_SR, and PROTOBUF, then multiple schemas will be registered under a single subject name. If these schemas are not backward compatible to each other, the connector will fail until you change the schema compatibility in Confluent Cloud Schema Registry.
"connection.host": The MongoDB host with connection string options. Use a hostname address and not a full URL. For example, use cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary for MONGODB_ATLAS and 54.190.171.123:27017/?authSource=admin for MONGODB_SELF_MANAGED.

Note

The connector does not support following connection string options in connection.host config: tlsCertificateKeyFile, tlsCertificateKeyFilePassword, tlsCAFile, tlsAllowInvalidCertificates, tlsInsecure, tlsAllowInvalidHostnames, authMechanism, authMechanismProperties, gssapiServiceName.
Other options like readPreference, readConcernLevel, or w defined in MongoDB Connection String Options can be configured in connection.host configuration. For example, cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&readConcernLevel=local&appName=test&w=majority.
The connector supports connecting to self-managed MongoDB database.
Use mongodb.instance.type as MONGODB_SELF_MANAGED and specify the connection.host accordingly to connect to self-managed instance. For example, 54.190.171.123:27017/?authSource=admin.

(Optional) "collection": The collection name. If the property is not used, all collections are watched in the supplied database.
(Optional) "poll.await.time.ms": The amount of time to wait before checking for new results in the change stream. If not used, this property defaults to 5000 ms (5 seconds).
(Optional) "poll.max.batch.size": The maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector. If not used, this property defaults to 100 records.
(Optional) "pipeline": An array of JSON objects that represents the pipeline operations to filter or modify the change stream output. For example: [{"$match": {"ns.coll": {"$regex": /^(collection1|collection2)$/}}}] sets the connector to listen to the collection1 and collection2 collections only. If not used, this property defaults to an empty array.
(Optional) "startup.mode": Specifies how the connector should start up when there is no source offset available. Resuming a change stream requires a resume token, which the connector gets from the source offset. If no source offset is available, the connector may either ignore all or some of the existing source data, or may at first copy all existing source data and then continue with processing new data. When set to latest (default), the connector ignores all existing source data. If set to timestamp, the connector actuates startup.mode.timestamp.* properties. If no properties are configured, timestamp is equivalent to latest. If startup.mode=copy_existing, the connector copies all existing source data to Change Stream events. This setting is equivalent to the deprecated setting copy.existing=true.
(Optional) "startup.mode.timestamp.start.at.operation.time": Actuated only if startup.mode=timestamp. Specifies the starting point for the change stream. Accepted values can be an integer number of seconds since the Epoch in decimal format (for example, 30), or an instant in the ISO-8601 format with one second precision (for example, 1970-01-01T00:00:30Z), or a BSON Timestamp in the canonical extended JSON (v2) format (for example, {"$timestamp": {"t": 30, "i": 0}})
(Optional) "startup.mode.copy.existing.namespace.regex": Regex that matches the namespaces from which the existing documents are copied. A namespace is represented as databaseName.collectionName. For example, stats\.page.* matches all collections that start with page in the stats database.
(Optional) "startup.mode.copy.existing.pipeline": An array of JSON objects that describes the pipeline operations to run when copying existing data. It is applied to existing documents that are being copied. If not used, this property defaults to an empty array.
(Optional) "publish.full.document.only": Set whether to return only the fullDocument field from the change stream event document produced by any update event. The fullDocument field contains the most current version of the updated document. Sets the change.stream.full.document=updateLookup setting so updated documents will be included.

Note

This automatic configuration only occurs at the time of connector creation. Changing this setting while the connector is already running will not retroactively apply or update the change.stream.full.document behavior.
(Optional) "publish.full.document.only.tombstone.on.delete": When set to true, the connector returns the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when publish.full.document.only is true.
(Optional) "change.stream.full.document": Determines what to return for update operations when using a Change Stream. The default setting returns the differences between the original document and the updated document. When set to updateLookup setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The whenAvailable setting returns the updated document, if available. The required setting returns the updated document and raises an error if it is not available.
(Optional) "change.stream.full.document.before.change": Configures the document pre-image your change stream returns on update operations. The default setting suppresses the document pre-image. When set to whenAvailable setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. When set to required setting returns the document pre-image and raises an error if it is not available.

"output.data.format": Sets the output Kafka record value format (data coming from the connector). Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, STRING or BSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

It chooses the appropriate converter and populates the derived settings output.format.key and output.format.value according to the table shown below.

`output.data.format`	Converter	`output.format.key`	`output.format.value`
`AVRO`	AvroConverter	schema	schema
`JSON_SR`	JsonSchemaConverter	schema	schema
`PROTOBUF`	ProtobufConverter	schema	schema
`JSON`	JsonConverter	schema	schema
`STRING`	StringConverter	json	json
`BSON`	ByteArrayConverter	bson	bson

If you select AVRO, be sure to set Compatibility mode (schema.compatibility.level) to NONE in Schema Registry. Note that schemas are generated per document in isolation. If not set to NONE, there is a chance that the new schema generated for the new document will not be backward compatible with previous versions of the schema.

(Optional) "heartbeat.interval.ms": The number of milliseconds the connector waits between sending heartbeat messages. If not used, this property defaults to 0. Thus, no heartbeat message is sent by default. If set to a positive number, the connector sends heartbeat messages when source records are not published in the specified interval. This mechanism improves resumability of the connector for low volume namespaces. See the Invalid Resume Token page in MongoDb documentation for more information on this feature. When using SMTs, use predicates to prevent SMTs from processing the heartbeat messages. For example, if the heartbeat topic name is __mongodb_heartbeats and the connector is writing the actual database records into topics that do not share common prefix with the heartbeat topic; use the following configuration to prevent heartbeat messages from being processed by the transform with an alias say, mongoTransform: "predicates": "isHeartbeatTopicPrefix", "predicates.isHeartbeatTopicPrefix.type": "org.apache.kafka.connect.transforms.predicates.TopicNameMatches", "predicates.isHeartbeatTopicPrefix.pattern": "__mongodb.*", "transforms.mongoTransform.predicate": "isHeartbeatTopicPrefix", "transforms.mongoTransform.negate": "true".
(Optional) "heartbeat.topic.name": The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the heartbeat.interval.ms setting to enable this feature. If setting the heartbeat messages for multiple connectors, you must ensure that the heartbeat topic names for the connectors are unique. If not set, this defaults to __mongodb_heartbeats.
"tasks.max": The connector supports running a single task.

Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.

See Configuration Properties for all property values and definitions.

Step 4: Load the properties file and create the connector

Enter the following command to load the configuration and start the connector:

confluent connect cluster create --config-file <file-name>.json

For example:

confluent connect cluster create --config-file mongo-db-source.json

Example output:

Created connector confluent-mongodb-source lcc-ix4dl

Step 5: Check the connector status

Enter the following command to check the connector status:

confluent connect cluster list

Example output:

ID          |            Name           | Status  | Type
+-----------+---------------------------+---------+-------+
lcc-ix4dl   | confluent-mongodb-source  | RUNNING | source

Step 6: Check the Kafka topic.

After the connector is running, verify that MongoDB documents are populating the Kafka topic. If the config startup.mode=copy_existing and the connector restarts due to any reason, you may see duplicate records in the topic.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Configuration Properties

Use the following configuration properties with the fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors for Confluent Platform.

How should we connect to your data?

name

Sets a name for your connector.

Type: string
Valid Values: A string at most 64 characters long
Importance: high

Kafka Cluster credentials

kafka.auth.mode

Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.

Type: string
Default: KAFKA_API_KEY
Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
Importance: high

kafka.api.key

Kafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.

Type: password
Importance: high

kafka.service.account.id

The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.

Type: string
Importance: high

kafka.api.secret

Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.

Type: password
Importance: high

Schema Config

schema.context.name

Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.

Type: string
Default: default
Importance: medium

How do you want to name your topic(s)?

topic.prefix

Prefix to prepend to table names to generate the name of the Apache Kafka® topic to publish data to.

Type: string
Importance: high

topic.namespace.map

JSON object that maps change stream document namespaces to topics. Any prefix configuration will still apply. In case multiple collections with records having varying schema are mapped to single topic with AVRO, JSON_SR, and PROTOBUF, then multiple schemas will be registered under single subject name. If these schemas are not backward compatible to each other, the connector will fail until you change the schema compatibility in Confluent Cloud Schema Registry.

Type: string
Default: “”
Importance: low

How should we connect to your MongoDB database?

mongodb.instance.type

Specifies the type of MongoDB instance the connector will connect to.

Type: string
Default: MONGODB_ATLAS
Valid Values: MONGODB_ATLAS, MONGODB_SELF_MANAGED
Importance: high

mongodb.auth.mechanism

Choose an authentication mechanism for MongoDB. Use SCRAM-SHA-256 for username/password authentication. Use MONGODB-X509 for certificate-based authentication. For MONGODB-X509, you must configure the SSL keystore properties.

Type: string
Default: SCRAM-SHA-256
Valid Values: MONGODB-X509, SCRAM-SHA-256
Importance: high

connection.host

For MongoDB Atlas, provide the SRV connection host (e.g., mycluster.abc123.mongodb.net). For Self Managed MongoDB, provide the host and port in MongoDB URI format, e.g., host1:27017 or host1:27017/?replicaSet=myReplicaSet.

Type: string
Default: “”
Importance: high

connection.user

MongoDB connection user.

Type: string
Importance: high

connection.password

MongoDB connection password.

Type: password
Importance: high

connection.ssl.truststore.file

The trust store file containing trusted certificates. Supported formats include JKS and PKCS12. If not set, the default Java trust store is used.

Type: password
Default: [hidden]
Importance: medium

connection.ssl.truststorePassword

The password for the trust store file.

Type: password
Default: [hidden]
Importance: medium

connection.ssl.keystore.file

The key store file containing the client certificate and private key for MONGODB-X509 authentication. Supported formats include JKS and PKCS12.

Type: password
Default: [hidden]
Importance: medium

connection.ssl.keystorePassword

The password for the key store file. This is optional for the client and only needed if connection.ssl.keystore.file is configured.

Type: password
Default: [hidden]
Importance: medium

database

MongoDB database name.

Type: string
Importance: high

Database details

collection

MongoDB collection name.

Type: string
Importance: medium

Connection details

poll.await.time.ms

The amount of time to wait before checking for new results on the change stream.

Type: int
Default: 5000 (5 seconds)
Valid Values: [1,…]
Importance: low

poll.max.batch.size

Maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.

Type: int
Default: 100
Valid Values: [1,…,1000]
Importance: low

pipeline

An array of JSON objects describing the pipeline operations to filter or modify the change events output. For example, [{“$match”: {“ns.coll”: {“$regex”: /^(collection1|collection2)$/}}}] will set your source connector to listen to the “collection1” and “collection2” collections only.

Type: string
Default: []
Importance: medium

startup.mode

Specifies how the connector should start up when there is no source offset available. If set to ‘latest’, the connector ignores all existing source data. If set to ‘timestamp’, the connector actuates startup.mode.timestamp.* properties. If no properties are configured, timestamp is equivalent to latest. If startup.mode=copy_existing, the connector copies all existing source data to Change Stream events.

Type: string
Default: “”
Importance: high

startup.mode.copy.existing.namespace.regex

Regular expression that matches the namespaces (databaseName.collectionName) from which to copy data. For example, stats.page.* matches all collections that starts with “page” in “stats” database.

Type: string
Default: “”
Importance: medium

startup.mode.copy.existing.pipeline

An array of JSON objects describing the pipeline operations to run when copying existing data. It will only be applied for existing documents which are being copied.

Type: string
Default: “”
Importance: medium

startup.mode.timestamp.start.at.operation.time

Actuated only if startup.mode=timestamp. Specifies the starting point for the change stream.

Type: string
Default: “”
Importance: medium

batch.size

The number of documents to return in a batch.

Type: int
Default: 0
Valid Values: […,50]
Importance: low

output.schema.key

The Avro schema definition for the key value of the SourceRecord.

Type: string
Default: { “type”: “record”, “name”: “keySchema”, “fields”: [{ “name”: “_id”, “type”: “string”}]}
Valid Values: A string at most 100000 characters long
Importance: medium

output.schema.value

The Avro schema definition for the value of the SourceRecord.

Type: string
Default: {“name”: “ChangeStream”, “type”: “record”, “fields”: [{“name”: “_id”, “type”: “string”}, {“name”: “operationType”, “type”: [“string”, “null”]}, {“name”: “fullDocumentBeforeChange”, “type”: [“string”, “null”]}, {“name”: “fullDocument”, “type”: [“string”, “null”]}, {“name”: “ns”, “type”: [{“name”: “ns”, “type”: “record”, “fields”: [{“name”: “db”, “type”: “string”}, {“name”: “coll”, “type”: [“string”, “null”]}]}, “null”]}, {“name”: “to”, “type”: [{“name”: “to”, “type”: “record”, “fields”: [{“name”: “db”, “type”: “string”}, {“name”: “coll”, “type”: [“string”, “null”]}]}, “null”]}, {“name”: “documentKey”, “type”: [“string”, “null”]}, {“name”: “updateDescription”, “type”: [{“name”: “updateDescription”, “type”: “record”, “fields”: [{“name”: “updatedFields”, “type”: [“string”, “null”]}, {“name”: “removedFields”, “type”: [{“type”: “array”, “items”: “string”}, “null”]}]}, “null”]}, {“name”: “clusterTime”, “type”: [“string”, “null”]}, {“name”: “txnNumber”, “type”: [“long”, “null”]}, {“name”: “lsid”, “type”: [{“name”: “lsid”, “type”: “record”, “fields”: [{“name”: “id”, “type”: “string”}, {“name”: “uid”, “type”: “string”}]}, “null”]}]}
Valid Values: A string at most 100000 characters long
Importance: medium

Producer configuration

linger.ms

Artificial delay for records to be sent together.

Type: long
Default: 0
Valid Values: [0,…,20000]
Importance: medium

producer.batch.size

Record batch size in bytes.

Type: int
Default: 16384
Valid Values: [0,…,491520]
Importance: medium

Output messages

output.data.format

Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, STRING or BSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF

Type: string
Default: STRING
Importance: high

output.key.format

Sets the output Kafka record key format. Valid entries are AVRO, JSON_SR, PROTOBUF, STRING or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF

Type: string
Default: STRING
Valid Values: AVRO, JSON, JSON_SR, PROTOBUF, STRING
Importance: high

publish.full.document.only

Only publish the changed document instead of the full change stream document. Sets the change.stream.full.document=updateLookup automatically so updated documents will be included.

Type: boolean
Default: false
Importance: high

publish.full.document.only.tombstone.on.delete

Return the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when publish.full.document.only is true

Type: boolean
Default: false
Importance: high

change.stream.full.document

Determines what to return for update operations when using a Change Stream. When set to ‘updateLookup’ setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The ‘whenAvailable’ setting returns the updated document, if available. The ‘required’ setting returns the updated document and raises an error if it is not available.

Type: string
Default: default
Importance: high

change.stream.full.document.before.change

Configures the document pre-image your change stream returns on update operations. When set to ‘whenAvailable’ setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. When set to ‘required’ setting returns the document pre-image and raises an error if it is not available.

Type: string
Default: default
Importance: high

change.stream.document.key.as.key

Use the document key as the source record key.

Type: boolean
Default: false
Importance: medium

change.stream.show.expanded.events

Determines if change streams notifies for DDL events, such as createIndexes and dropIndexes events. This functionality is new in version 6.0. See MongoDB documentation for more details on showExpandedEvents. This setting is required to show updateDescription.disambiguatedPaths in update events, helping clarify changes that involve ambiguous fields. This specific feature is new in version 6.1. See MongoDB documentation for more details on disambiguatedPaths.

Type: boolean
Default: false
Importance: medium

collation

The JSON representation of the collation options to use for the change stream. Use the Collation.asDocument().toJson() to create the specific json representation.

Type: string
Default: “”
Importance: high

output.json.format

The output format of json strings can be configured to be either: DefaultJson: The legacy strict json formatter. ExtendedJson: The fully type safe extended json formatter. SimplifiedJson: Simplified Json, with ObjectId, Decimals, Dates and Binary values represented as strings. Users can provide their own implementation of the com.mongodb.kafka.connect.source.json.formatter.

Type: string
Default: DefaultJson
Importance: high

topic.separator

Separator to use when joining prefix, database, collection, and suffix values. This generates the name of the Kafka topic to publish data to. Used by the ‘DefaultTopicMapper’.

Type: string
Default: .
Importance: low

topic.suffix

Suffix to append to database and collection names to generate the name of the Kafka topic to publish data to.

Type: string
Importance: low

output.schema.infer.value

Whether the connector should infer the schema for the value document of the Source Record. Since the connector processes each document in isolation, the connector may generate many schemas. The connector only reads this setting when you set your ‘Output Kafka record value format’ setting to AVRO, JSON, JSON_SR and PROTOBUF.

Type: boolean
Default: true
Importance: low

Error handling

heartbeat.interval.ms

The number of milliseconds the connector waits between sending heartbeat messages. The connector sends heartbeat messages when source records are not published in the specified interval. This mechanism improves resumability of the connector for low volume namespaces. When using SMTs, use predicates to prevent SMTs from processing the heartbeat messages. See connector documentation for more details.

Type: int
Default: 0
Importance: medium

heartbeat.topic.name

The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the “heartbeat.interval.ms” setting to enable this feature.

Type: string
Default: __mongodb_heartbeats
Importance: medium

remove.field.on.schema.mismatch

If true, remove fields from the document that are not present in the schema. Otherwise, throw an error or send the documents to the DLQ depending on the value of errors.tolerance being set to ALL or NONE respectively.

Type: boolean
Default: true
Importance: medium

mongo.errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework’s.

Type: string
Default: NONE
Importance: medium

mongo.errors.deadletterqueue.topic.name

Whether to output conversion errors to the dead letter queue. Stops poison messages when using schemas, any message will be outputted as extended json on the specified topic. By default messages are not outputted to the dead letter queue. Also requires errors.tolerance=all.

Type: string
Importance: medium

offset.partition.name

The custom offset partition name to use. You can use this option to instruct the connector to start a new change stream when an existing offset contains an invalid resume token. If you leave this setting blank, the connector uses the default partition name based on the connection details.

Type: string
Default: “”
Importance: medium

Server API

server.api.version

The server API version to use. Disabled by default.

Type: string
Importance: low

server.api.deprecation.errors

Sets whether the connector requires use of deprecated server APIs to be reported as errors.

Type: boolean
Default: false
Importance: low

server.api.strict

Sets whether the application requires strict server API version enforcement.

Type: boolean
Default: false
Importance: low

Number of tasks for this connector

tasks.max

Maximum number of tasks for the connector.

Type: int
Valid Values: [1,…,1]
Importance: high

Additional Configs

header.converter

The converter class for the headers. This is used to serialize and deserialize the headers of the messages.

Type: string
Importance: low

producer.override.compression.type

The compression type for all data generated by the producer. Valid values are none, gzip, snappy, lz4, and zstd.

Type: string
Importance: low

producer.override.linger.ms

The producer groups together any records that arrive in between request transmissions into a single batched request. More details can be found in the documentation: https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms.

Type: long
Valid Values: [100,…,1000]
Importance: low

value.converter.allow.optional.map.keys

Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.auto.register.schemas

Specify if the Serializer should attempt to register the Schema.

Type: boolean
Importance: low

value.converter.connect.meta.data

Allow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.enhanced.avro.schema.support

Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.enhanced.protobuf.schema.support

Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.flatten.unions

Whether to flatten unions (oneofs). Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.generate.index.for.unions

Whether to generate an index suffix for unions. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.generate.struct.for.nulls

Whether to generate a struct variable for null values. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.int.for.enums

Whether to represent enums as integers. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.latest.compatibility.strict

Verify latest subject version is backward compatible when use.latest.version is true.

Type: boolean
Importance: low

value.converter.object.additional.properties

Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.

Type: boolean
Importance: low

value.converter.optional.for.nullables

Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.optional.for.proto2

Whether proto2 optionals are supported. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.scrub.invalid.names

Whether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.

Type: boolean
Importance: low

value.converter.use.latest.version

Use latest version of schema in subject for serialization when auto.register.schemas is false.

Type: boolean
Importance: low

value.converter.use.optional.for.nonrequired

Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.

Type: boolean
Importance: low

value.converter.wrapper.for.nullables

Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.wrapper.for.raw.primitives

Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.

Type: boolean
Importance: low

errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior. WARNING: This property should be used with CAUTION for SOURCE CONNECTORS as it may lead to dataloss. If you set this property to ‘all’, the connector will not fail on errant records, but will instead log them (and send to DLQ for Sink Connectors) and continue processing. If you set this property to ‘none’, the connector task will fail on errant records.

Type: string
Default: none
Importance: low

key.converter.key.subject.name.strategy

How to construct the subject name for key schema registration.

Type: string
Default: TopicNameStrategy
Importance: low

key.converter.replace.null.with.default

Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Key Converter.

Type: boolean
Default: true
Importance: low

key.converter.schemas.enable

Include schemas within each of the serialized keys. Input message keys must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Key Converter.

Type: boolean
Default: false
Importance: low

value.converter.decimal.format

Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:

BASE64 to serialize DECIMAL logical types as base64 encoded binary data and

NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.

Type: string
Default: BASE64
Importance: low

value.converter.flatten.singleton.unions

Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.

Type: boolean
Default: false
Importance: low

value.converter.ignore.default.for.nullables

When set to true, this property ensures that the corresponding record in Kafka is NULL, instead of showing the default column value. Applicable for AVRO,PROTOBUF and JSON_SR Converters.

Type: boolean
Default: false
Importance: low

value.converter.reference.subject.name.strategy

Set the subject reference name strategy for value. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. Note that the subject reference name strategy can be selected only for PROTOBUF format with the default strategy being DefaultReferenceSubjectNameStrategy.

Type: string
Default: DefaultReferenceSubjectNameStrategy
Importance: low

value.converter.replace.null.with.default

Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.

Type: boolean
Default: true
Importance: low

value.converter.schemas.enable

Include schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.

Type: boolean
Default: false
Importance: low

value.converter.value.subject.name.strategy

Determines how to construct the subject name under which the value schema is registered with Schema Registry.

Type: string
Default: TopicNameStrategy
Importance: low

Auto-restart policy

auto.restart.on.user.error

Enable connector to automatically restart on user-actionable errors.

Type: boolean
Default: true
Importance: medium

Egress allowlist

connector.egress.whitelist

Type: string
Default: “”
Importance: high

Next Steps

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud for Apache Flink, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.

Get Started with the MongoDB Atlas Source Connector for Confluent Cloud

Features

Limitations

Maximum message size

Manage custom offsets

JSON payload

Quick Start

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster

Step 2: Add a connector

Step 3: Select your connector

Step 4: Enter the connector details

Step 5: Check the Kafka topic

Using the Confluent CLI

Step 1: List the available connectors

Step 2: List the connector configuration properties

Step 3: Create the connector configuration file

Step 4: Load the properties file and create the connector

Step 5: Check the connector status

Step 6: Check the Kafka topic.

Configuration Properties

How should we connect to your data?

Kafka Cluster credentials

Schema Config

How do you want to name your topic(s)?

How should we connect to your MongoDB database?

Database details

Connection details

Producer configuration

Output messages

Error handling

Server API

Number of tasks for this connector

Additional Configs

Auto-restart policy

Egress allowlist

Suggested Reading

Next Steps