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

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.

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:

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.

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.

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:

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.

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

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.

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