# MongoDB CDC Source (Debezium) Connector for Confluent Cloud The fully managed MongoDB Change Data Capture Source (Debezium) connector for Confluent Cloud streams data from MongoDB replica sets and sharded clusters to Apache Kafka® topics. It performs an initial snapshot of existing data, then monitors for later document-level changes. Using Confluent Cloud Schema Registry, the connector supports Avro, JSON Schema, and Protobuf output formats, ensuring structured data delivery from your MongoDB collections into dedicated Apache Kafka® topics. This automated pipeline captures inserts, updates, and deletes as real-time event streams, making database modifications immediately available for downstream applications and microservices without complex polling logic. 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](../networking/internet-resource.md#clusters-connect-cloud). ## Features The MongoDB CDC Source (Debezium) connector provides the following features: * **Topics creation**: Automatically creates Kafka topics using the naming convention: `..`. The topics are created with the properties: `topic.creation.default.partitions=1` and `topic.creation.default.replication.factor=3`. For more information, see [Maximum message size](#cc-mongodb-cdc-source-debezium-topic-sizing). * **Database authentication**: Uses password authentication or IAM (Identity and Access Management) role-based authentication through provider integration. * **IAM role-based authentication**: Eliminates static database credentials by supporting AWS IAM authentication for MongoDB Atlas through Confluent Cloud provider integrations. * **SSL support**: Supports SSL encryption when configured to establish an encrypted connection to the MongoDB server. * **Databases included and excluded**: Sets whether a database is or is not monitored for change captures. By default, the connector monitors every database on the server. * **Collections included and excluded**: Sets whether a collection is or is not monitored for changes. By default, the connector monitors every non-system collection. * **Tombstones on delete**: Sets whether a tombstone event is generated after a delete event. Default is `true`. * **Output formats**: Supports the following Kafka record formats: * Value: JSON (Schemaless), Avro, JSON Schema, or Protobuf * Key: JSON (Schemaless), Avro, JSON Schema, Protobuf, or String [Schema Registry](../../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format. * **Client-side encryption (CSFLE and CSPE) support**: Supports CSFLE and CSPE for sensitive data. For more information about CSFLE or CSPE setup, see [Manage CSFLE or CSPE for connectors](../csfle.md#connect-csfle). * **Secret manager integration**: The connector supports secret manager integration. For `Password` based authentication, the connector can retrieve the following configurations from an integrated secret manager at runtime as needed. | **Secret manager managed configuration** | **Type** | |--------------------------------------------|------------| | `mongodb.user` | `STRING` | | `mongodb.password` | `PASSWORD` | For more information, see [Create a secret manager integration in Confluent Cloud](../secret-manager-integration/overview.md#cloud-secret-manager-quickstart). For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](../connect-api-section.md#ccloud-connect-api) section. ## Supported database versions The MongoDB CDC Source (Debezium) connector is compatible with MongoDB versions 4.4 through 8.0. ## Limitations * For connector limitations, see [MongoDB CDC Source (Debezium) Connector](../limits.md#cc-mongodb-cdc-source-limits). * If you plan to use one or more Single Message Transformations (SMTs), see [SMT Limitations](../single-message-transforms.md#cc-single-message-transforms-limitations). ## 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](../../clusters/cluster-types.md#cloud-cluster-types). ## Oplog retention during snapshot When launched, the CDC connector creates a snapshot of the existing data in the database to capture the specified collections. To do this, the connector reads all documents from the included collections. Completing the snapshot can take a while if one or more of the specified collections is very large. During the snapshot process, the database server must retain the oplog (operations log) so that when the snapshot is complete, the CDC connector can start processing database changes that have occurred since the snapshot process began. If one or more of the collections are very large, the snapshot process could run longer than the oplog retention window configured on the database server. To capture very large collections, ensure the oplog is sized large enough to retain changes for the duration of the snapshot. For MongoDB Atlas, you can configure the oplog window in the cluster settings. For self-managed deployments, increase the oplog size using the `replSetResizeOplog` command. ## 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](../offsets.md#connect-custom-offsets). **To manage offsets**: - Manage offsets using Confluent Cloud APIs. For more information, see [Connect offsets API reference](https://docs.confluent.io/cloud/current/ccloud/offsets-connect-v-1/). ### Get the current offset To get the current offset, make a `GET` request that specifies the environment, Kafka cluster, and connector name. ```bash GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets Host: https://api.confluent.cloud ``` Use your Cloud Resource Management API key and secret for basic authentication in your curl request. **Response:** Successful calls return HTTP `200` with a JSON payload that describes the offset. ```bash { "id": "lcc-example123", "name": "{connector_name}", "offsets": [ { "partition": { "server_id": "testing" }, "offset": { "ord": 1, "resume_token": "zQAAAAJfZGF0YQC9AAAAODI2OUQ3QzE0RTAwMDAwMDBBMkIwNDJDMDEwMDI5NkU1QTEwMDQ5NjczMzlBMjZCMjQ0NkY2QjdDODVCMkM2REJFRTI4RjQ2M0M2RjcwNjU3MjYxNzQ2OTZGNkU1NDc5NzA2NTAwM0M2OTZFNzM2NTcyNzQwMDQ2NjQ2RjYzNzU2RDY1NkU3NDRCNjU3OTAwNDY2NDVGNjk2NDAwNjQ2OUQ3QzE0RTE4NkI3RkFDQzI4NDUxRjkwMDAwMDQAAA==", "sec": 177574740 } } ], "metadata": { "observed_at": "2024-03-28T17:57:48.139635200Z" } } ``` Responses include the following information: - The connector information (`id` and `name`). - The `server_id` in the partition, identifying the MongoDB server from which the event originated. - The offset position, including `resume_token` (MongoDB change stream resume token), `ord`, and `sec`. - 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 fetches more recently observed offsets. **Retrieving resume tokens from MongoDB** You can retrieve resume tokens directly from MongoDB change streams using the following commands: ```javascript var cs = db.my_collection.watch() db.my_collection.insertOne({ name: "Test User", ts: new Date() }); var change = cs.next(); print("Resume Token (hex): " + change._id._data); cs.close(); ``` **Converting resume tokens** The connector requires resume tokens to be Base64-encoded. However, MongoDB change streams provide them in hexadecimal format. Use the following commands in your terminal to convert between these formats: **Base64 to MongoDB hexadecimal format:** ```bash echo "$CONNECTOR_BASE64_RESUME_TOKEN" | base64 -d | strings ``` **MongoDB hexadecimal to Base64 format:** ```bash python3 -c "import base64,struct; t='MONGO_HEX_RESUME_TOKEN'; s=t.encode()+b'\x00'; b=b'\x02'+b'_data\x00'+struct.pack(' Prerequisites : - Authorized access to a [Confluent Cloud](https://www.confluent.io/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](https://docs.confluent.io/confluent-cli/current/install.html). - [Schema Registry](../../get-started/schema-registry.md#cloud-sr-config) enabled to use a Schema Registry-based format (Avro, JSON_SR (JSON Schema), or Protobuf). - Network access configured to reach your MongoDB deployment. For networking considerations, see [Networking and DNS](../overview.md#connect-internet-access-resources). To use a set of public egress IP addresses, see [Public Egress IP Addresses for Confluent Cloud Connectors](../static-egress-ip.md#cc-static-egress-ips). The following example shows the AWS Management Console when setting up security group rules for the VPC.
- Kafka cluster credentials. The following lists the different ways you can provide credentials. - Enter an existing [service account](../service-account.md#s3-cloud-service-account) resource ID. - Create a Confluent Cloud [service account](../service-account.md#s3-cloud-service-account) for the connector. Make sure to review the ACL entries required in the [service account documentation](../service-account.md#s3-cloud-service-account). 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](https://docs.confluent.io/confluent-cli/current/command-reference/api-key/confluent_api-key_create.html) *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](../../get-started/index.md#cloud-create-kafka-cluster). #### 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 CDC Source** connector card.  #### Step 4: Enter the connector details At the **MongoDB CDC Source (Debezium) Connector** screen, complete the following: #### NOTE * Ensure you have all your [prerequisites](#cc-mongodb-cdc-source-debezium-prereqs) completed. ### Define a topic prefix 1. In the **Topic prefix** field, define a topic prefix your connector will use to publish to Kafka topics. The connector publishes Kafka topics using the following naming convention: ``. #### IMPORTANT If you are configuring granular access using a [service account](../service-account.md#s3-cloud-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](../managed-connector-rbac.md#managed-connector-rbac). To add ACLs, you use the (\*) wildcard in the ACL entries as shown in the following examples. ```bash confluent kafka acl create --allow --service-account "" --operation create --topic "*" ``` ```bash confluent kafka acl create --allow --service-account "" --operation write --topic "*" ``` 2. Click **Continue**. ### Kafka access 1. 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](../service-account.md#s3-cloud-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. 2. Click **Continue**. ### Authentication 1. Configure the authentication properties: **Authentication method** - **Authentication method**: Select the authentication mechanism for the MongoDB database. Supported options are: * `Password`: Default. Uses standard username and password credentials. * `IAM Roles`: Uses AWS IAM authentication for MongoDB Atlas. - **Use secret manager**: Fetch sensitive configuration values from a secret manager. - **Provider Integration**: Select an existing provider integration that has access to your MongoDB Atlas cluster. **Secret manager configuration** - **Secret manager**: Select the secret manager to use for retrieving sensitive data. - **Configurations from Secret manager**: Select the configurations whose values Confluent Cloud should fetch from the secret manager. - **Provider Integration**: Select an existing provider integration that has access to your MongoDB Atlas cluster. **How should we connect to your database?** - **MongoDB connection string**: Enter the MongoDB connection string in the format `mongodb://host:port` or `mongodb+srv://cluster.example.com`. Do not include credentials here. Use the specific user, password, or provider integration fields instead. - **User**: Enter a MongoDB username with `readAnyDatabase` role and `changeStream` privileges. For sharded clusters, the user also requires `read` access to the `config` and `local` databases. If enabling incremental snapshots, ensure the user has write access to the signal data collection. - **Password**: Enter the password for the specified MongoDB database user. - **Enable SSL connection to MongoDB**: Determines whether to enable an SSL/TLS encrypted connection to MongoDB. Supported options are: * `true`: Enables an SSL/TLS encrypted connection. * `false` (default): Disables SSL/TLS encryption. - **SSL Truststore**: Provide the trust store file containing trusted certificates in JKS or PKCS12 format. This is required when TLS is enabled. When using Confluent REST API or Confluent CLI, encode the file in base64 and use this format: `data:application/octet-stream;base64,`. - **SSL Truststore Password**: Enter the password required to access the SSL truststore. - **Allow invalid hostnames for SSL connection**: Determines whether to disable SSL hostname verification. Supported options are: * `true`: Disables SSL hostname verification. Use for development or testing only. * `false` (default): Enables SSL hostname verification. Recommended for production use. Setting this to `true` is not secure in production environments and may violate your organization’s security policies. Confluent Cloud connectors use TLS by default with strict hostname verification. - **Credentials Database**: Specify the database containing user credentials for authentication. This defaults to `admin`. 2. Click **Continue**. ### Configuration **Output messages** - **Select output record value format**: Set the output Kafka record value format. Valid entries are `AVRO`, `JSON_SR`, `PROTOBUF`, or `JSON`. #### NOTE You must have Confluent Cloud Schema Registry configured if you are using a schema-based message format like AVRO, JSON_SR, and PROTOBUF. - **Output Kafka record key format**: Set the output Kafka record key format. Valid entries are `AVRO`, `JSON_SR`, `PROTOBUF`, `STRING`, or `JSON`. #### NOTE You need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF. **Database config** - **Include Databases**: Provide a comma-separated list of databases to monitor. Supports regular expressions when `filters.match.mode` is `regex`. If empty, includes all databases in the `capture.scope`. Do not use this with `database.exclude.list`. - **Exclude Databases**: Provide a comma-separated list of database names to exclude. Supports regular expressions when `filters.match.mode` is `regex`. Do not use this with `database.include.list`. - **Include Collections**: Provide a comma-separated list of fully-qualified collections (`database.collection`) to capture. Supports regular expressions through `filters.match.mode`. Do not use this with `collection.exclude.list`. - **Exclude Collections**: Provide a comma-separated list of fully-qualified collections (`database.collection`) to exclude from data capture. - **Database and collection include/exclude match mode**: Determines the matching logic for include and exclude filters. Supported options are: * `regex`: Enables regular expression matching. * `literal`: Enables exact string matching. **Connector config** - **Capture mode**: Determines the mechanism for capturing document changes. Supported options are: * `change_streams`: Captures only modified fields. * `change_streams_update_full`: Captures the full document state (recommended). * `change_streams_with_pre_image`: Captures modified fields and includes the `before` state (requires MongoDB 6.0 or later versions). * `change_streams_update_full_with_pre_image`: Captures the full document state and includes pre-images (requires MongoDB 6.0 or later versions). - **Capture scope**: Define the boundary for data capture. Supported options are: * `deployment`: Captures changes from the entire cluster or replica set. * `database`: Captures changes from the database specified in `capture.target`. * `collection`: Captures changes from the collection specified in `capture.target`. - **Capture target**: Specify the target name when `capture.scope` is `database` or `collection`. Use the database name for `scope=database` or `database.collection` for `scope=collection`. The connector ignores this setting if the scope is `deployment`. **Snapshot Configs** - **Snapshot mode**: Set the behavior for initial data capture. Supported options are: * `initial`: Performs a snapshot only on the first connector start. * `no_data`: Skips the initial snapshot. * `when_needed`: Performs a snapshot only if offsets are missing or invalid. * `initial_only`: Performs a snapshot and then stops the connector. **Data encryption** - Enable **Client-Side Field Level Encryption** for data encryption. Specify a **Service Account** to access the Schema Registry and associated encryption rules or keys with that schema. For more information on CSFLE or CSPE setup, see [Manage encryption for connectors](../csfle.md#connect-csfle). ### **Show advanced configurations** **Additional configurations** To add an additional configuration, see [Additional Connector Configuration Reference for Confluent Cloud](../reference/connector-configuration.md#cc-config-connect). - **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?](../../sr/faqs-cc.md#faq-schema-contexts). **Additional Configs** - **Value Converter Replace Null With Default**: Specifies whether to replace fields that have a default value and that are null to the default value. When set to `true`, the connector uses the default value; otherwise, it uses `null`. Applies to the `JSON` converter. - **Value Converter Reference Subject Name Strategy**: Sets the subject reference name strategy for values. Valid entries are `DefaultReferenceSubjectNameStrategy` or `QualifiedReferenceSubjectNameStrategy`. You can use this strategy only with `PROTOBUF` format; the default strategy is `DefaultReferenceSubjectNameStrategy`. - **Value Converter Schemas Enable**: Includes schema within each of the serialized values. Input messages must contain `schema` and `payload` fields and must not contain additional fields. For plain `JSON` data, set this to `false`. Applies to the `JSON` converter. - **Errors Tolerance**: Use this property to configure the connector’s error handling behavior. #### WARNING Use this property with caution for sink connectors, as it can lead to data loss. If you set this property to `all`, the connector does not fail on errant records, but logs them (and sends to DLQ for sink connectors) and continues processing. If you set this property to `none`, the connector task fails on errant records. - **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. Applies to the `AVRO`, `PROTOBUF`, and `JSON_SR` converters. - **Value Converter Decimal Format**: Specifies the `JSON` or `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 `DECIMAL` logical type values in `JSON` or `JSON_SR` as a number representing the decimal value. - **Key Converter Schema ID Serializer**: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers. - **Value Converter Connect Meta Data**: Enables the Connect converter to add its metadata to the output schema. Applies to Avro converters. - **Value Converter Value Subject Name Strategy**: Determines how to construct the subject name under which the value schema is registered with Schema Registry. - **Key Converter Key Subject Name Strategy**: Determines how to construct the subject name for key schema registration. - **Value Converter Schema ID Serializer**: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers. - **Store transaction metadata information in a dedicated topic**: Determines whether the connector generates transaction boundary events and enriches change event envelopes with transaction metadata. Supported options are: * `true`: Generates transaction boundary events and enriches change event envelopes with transaction metadata. * `false`: Does not generate transaction boundary events. - **Transaction topic name**: Set the topic name for transaction metadata. The final name follows the pattern `.`. Defaults to `{{.logicalClusterId}}.transaction`. - **Pipeline stages applied to the change stream cursor**: Define a MongoDB aggregation pipeline as a JSON array to filter change stream events at the database level. - **Change stream cursor pipeline order**: Set the execution order for pipeline stages. Supported options are: * `internal_first`: Runs connector stages before user stages. * `user_first`: Runs user stages before connector stages. * `user_only`: Runs only user stages and bypasses connector stages. - **Oversize document handling mode**: Determines the strategy for handling BSON documents that exceed size limits. Supported options are: * `fail`: Stops the connector. * `skip`: Ignores the document. * `split`: Fragments large events. Requires MongoDB 6.0.9 or later. - **Poll interval (ms)**: Set the time in milliseconds to wait for new change events when no data is returned. Default is `500` ms. - **Heartbeat frequency ms**: Set the interval in milliseconds for the cluster monitor to detect membership changes in the replica set. Minimum value must be `500` ms. - **Enabled notification channels names**: Provide a comma-separated list of enabled channels. Supported options are: * `log`: Logs notifications. * `sink`: Sends notifications to the topic in `notification.sink.topic.name`. - **Notification topic name**: Set the Kafka topic name for notifications. This is required if `sink` is in the list of enabled channels. **Auto-restart policy** - **Enable Connector Auto-restart**: Enables 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. If disabled, you must manually restart the connector. **Output messages** - **After-state only**: Determines whether to emit only the document state after a change. Supported options are: * `true`: Emits only the document state after the change. * `false` (default): Emits the full Debezium envelope with operation metadata. - **Tombstones on delete**: Determines if the connector emits a tombstone event after a delete event. Supported options are: * `true` (default): Emits both the delete event and a tombstone for log compaction. * `false`: Emits only the delete event. **Database config** - **Exclude Fields**: Provide a comma-separated list of fully-qualified field names (`database.collection.field`) to exclude from data capture. - **Rename Fields**: Provide a comma-separated list of field rename mappings in the format `database.collection.oldName:newName`. **Connector config** - **Capture mode full update type**: Set the method for obtaining the full document for updates. Supported options are: * `lookup`: Performs a separate query. * `post_image`: Uses MongoDB post-images (requires MongoDB 6.0 or later versions). - **Field name adjustment mode**: Determines how to adjust field names for converter compatibility. Supported options are: * `none`: Applies no adjustment. * `avro`: Replaces invalid characters with underscores. * `avro_unicode`: Replaces invalid characters with unicode sequences. - **Schema name adjustment mode**: Determines how to adjust schema names for converter compatibility. Supported options are: * `none`: Applies no adjustment. * `avro`: Replaces invalid characters with underscores. * `avro_unicode`: Replaces invalid characters with unicode sequences. #### NOTE `_` is an escape sequence like backslash in Java. - **Heartbeat interval (ms)**: Set the frequency in milliseconds for sending heartbeat messages to Kafka. Set to `0` (default) to disable. Heartbeats monitor connector health and can reduce the volume of re-sent events upon restart. - **Skipped Operations**: Specify a comma-separated list of operations to skip. Supported options are: * `c`: Skips insert operations. * `u`: Skips update operations. * `d`: Skips delete operations. * `none`: Does not skip any operations. - **Change event batch size**: Set the number of events processed per batch. Choose a value between `1` and `5000`. Defaults to `2048`. **Snapshot Configs** - **Snapshot mode include data collection**: Provide a comma-separated list of collections to snapshot. This must be a subset of `collection.include.list`. - **Snapshot delay (milliseconds)**: Set the interval in milliseconds to wait before starting a snapshot after the connector starts. Default is `0ms`. **Schema Config** - **Key converter reference subject name strategy**: Set the subject reference name strategy for the key. Supported options are: * `DefaultReferenceSubjectNameStrategy` (default). * `QualifiedReferenceSubjectNameStrategy`. These options are selectable only for the `PROTOBUF` format. **Incremental Snapshot Configs** - **Incremental snapshot chunk size**: Set the maximum number of documents fetched per incremental snapshot chunk. Tune this based on available heap memory. Larger values improve throughput by reducing query overhead but increase memory consumption. - **Incremental snapshot watermarking strategy**: Set the strategy for watermarking during incremental snapshots. Supported options are: * `INSERT_INSERT` (default): Writes both open and close signals. * `INSERT_DELETE`: Writes the open signal and deletes it upon closing. **Streaming Configs** - **Streaming delay (milliseconds)**: Set the delay in milliseconds between completing a snapshot and starting streaming. Default is `60000` (1 minute). This buffer ensures offsets are committed and prevents duplicate snapshots on connector restart. **Signal Configs** - **Enabled channels names**: Provide a list of signaling channels to enable. Supported options are: * `source` (default): Reads signals from the database collection. * `kafka`: Consumes signals from a Kafka topic. #### NOTE `source` is required when using `kafka`. - **Signal data collection**: Specify the fully-qualified collection (`database.collection`) that stores control signals for snapshot operations. This setting is required when signal channels are configured. The connector monitors this collection for signal documents to trigger snapshot actions. The connector needs to have `write` permissions on this collection. - **Signal topic name**: Set the name of the Kafka topic the connector monitors for ad-hoc signals through the Confluent CLI. **Transforms** - **Single Message Transformations**: To add a new SMT, see [Add transforms](../single-message-transforms.md#cc-single-message-transforms-ui). For more information about unsupported SMTs, see [Unsupported transformations](../single-message-transforms.md#cc-single-message-transforms-unsupported-transforms). **Processing position** - **Set offsets**: Click **Set offsets** to define a specific offset for this connector to begin procession data from. For more information on managing offsets, see [Manage offsets](../offsets.md#connect-custom-offsets). For additional information about the Debezium SMTs `ExtractNewDocumentState` and `MongoEventRouter`, see [Debezium transformations](../single-message-transforms.md#cc-single-message-transforms-debezium-unwrap). For all property values and definitions, see [Configuration Properties](#cc-mongodb-cdc-source-config-properties). 1. Click **Continue**. ### Sizing The connector supports running a single task. Click **Continue**. ### Review and Launch 1. Verify the connection details by previewing the running configuration. 2. After you have validated that the properties are configured to your satisfaction, click **Launch**. The connector status should transition from **Provisioning** to **Running**. #### Step 5: Check the Kafka topic After the connector is running, verify that messages are populating your Kafka topic. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](../connect-api-section.md#ccloud-connect-api) section. ### Using the Confluent CLI Complete the following steps to set up and run the connector using the Confluent CLI. #### NOTE Ensure you have all your [prerequisites](#cc-mongodb-cdc-source-debezium-prereqs) completed. #### Step 1: List the available connectors Enter the following command to list available connectors: ```none confluent connect plugin list ``` #### Step 2: List the connector configuration properties Enter the following command to show the connector configuration properties: ```none confluent connect plugin describe ``` 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 examples show the required connector properties for both password and IAM role-based authentication. Using password authentication: ```none { "connector.class": "MongoDbCdcSource", "name": "MongoDBCdcSourceConnector_0", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "****************", "kafka.api.secret": "****************************************************************", "mongodb.connection.string": "mongodb+srv://clustername.12345.mongodb.net", "mongodb.password": "*********", "mongodb.user": "database-username", "topic.prefix": "mongodb", "collection.include.list": "employees.departments", "output.data.format": "JSON", "tasks.max": "1" } ``` Using IAM role-based authentication: ```none { "connector.class": "MongoDbCdcSource", "name": "MongoDBCdcSourceConnector_0", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "****************", "kafka.api.secret": "****************************************************************", "authentication.method": "IAM Roles", "provider.integration.id": "pint-12345", "mongodb.connection.string": "mongodb+srv://clustername.12345.mongodb.net", "topic.prefix": "mongodb", "collection.include.list": "employees.departments", "output.data.format": "JSON", "tasks.max": "1" } ``` The configuration properties have the following definitions: * `"connector.class"`: Sets the connector plugin name. * `"name"`: Sets a name for your new connector in the Kafka cluster to identify the connector in Confluent Cloud. * `"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](../service-account.md#s3-cloud-service-account), specify the **Resource ID** in the property `kafka.service.account.id=`. To list the available service account resource IDs, use the following command: ```bash confluent iam service-account list ``` For example: ```bash 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 ``` * `"authentication.method"`: Specifies the authentication mechanism for the MongoDB database. Valid entries are `Password` or `IAM Roles`. * `"provider.integration.id"`: Links the connector to a specific cloud provider configuration for secure, keyless authentication (used with IAM roles). * `"mongodb.connection.string"`: Defines the MongoDB connection string in the format `mongodb://host:port` or `mongodb+srv://cluster.example.com` to locate the MongoDB deployment. * `"mongodb.password"`: Provides the secret credential associated with the defined MongoDB user. * `"mongodb.user"`: Defines the specific MongoDB username that has the required authorization. * `"topic.prefix"`: Provides a namespace for the particular database server or cluster that the connector captures changes from. * `"collection.include.list"`: Provides a comma-separated list of fully-qualified collections (`database.collection`) to capture. * `"output.data.format"`: Sets the output Kafka record value format (data coming from the connector). Valid entries are `AVRO`, `JSON_SR`, `JSON`, or `PROTOBUF`. You must have Confluent Cloud Schema Registry configured if using a schema-based record format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF). * `"tasks.max"`: Provides the number of [tasks](/platform/current/connect/concepts.html#tasks) in use by the connector. You can run multiple connectors with a limit of one task per connector (that is, `"tasks.max": "1"`). #### NOTE To enable CSFLE or CSPE for data encryption, specify the following properties: * `csfle.enabled`: Flag to indicate whether the connector honors CSFLE or CSPE rules. * `sr.service.account.id`: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema. For more information on CSFLE or CSPE setup, see [Manage encryption for connectors](../csfle.md#connect-csfle). **SMTs**: For details about adding SMTs using the Confluent CLI, see the [Single Message Transformations](../single-message-transforms.md#cc-single-message-transforms) documentation. For additional information about the Debezium SMTs `ExtractNewDocumentState` and `MongoEventRouter`, see [Debezium transformations](../single-message-transforms.md#cc-single-message-transforms-debezium-unwrap). See [Configuration Properties](#cc-mongodb-cdc-source-config-properties) for all properties and definitions. #### Step 4: Load the properties file and create the connector Enter the following command to load the configuration and start the connector: ```none confluent connect cluster create --config-file .json ``` For example: ```none confluent connect cluster create --config-file mongodb-cdc-source.json ``` Example output: ```none Created connector MongoDbCdcSourceConnector_1 lcc-ix4dl ``` #### Step 5: Check the connector status Enter the following command to check the connector status: ```none confluent connect cluster list ``` Example output: ```none ID | Name | Status | Type +-----------+-------------------------------+---------+-------+ lcc-ix4dl | MongoDbCdcSourceConnector_1 | RUNNING | source ``` #### Step 6: Check the Kafka topic After the connector is running, verify that messages are populating your Kafka topics. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](../connect-api-section.md#ccloud-connect-api) section. ## Configuration Properties Use the following configuration properties with the fully managed connector. ### Authentication method `authentication.method` : Select the authentication mechanism for the MongoDB database.
`Password` uses standard username and password credentials.
`IAM Roles` uses AWS IAM authentication for MongoDB Atlas.
* Type: string * Default: Password * Valid Values: IAM Roles, Password * Importance: high `secret.manager.enabled` : Fetch sensitive configuration values from a secret manager.
* Type: boolean * Default: false * Importance: high `provider.integration.id` : Select an existing provider integration that has access to your MongoDB Atlas cluster.
* Type: string * Importance: high ### Secret manager configuration `secret.manager` : Select the secret manager to use for retrieving sensitive data.
* Type: string * Importance: high `secret.manager.managed.configs` : Select the configurations to fetch their values from the secret manager.
* Type: list * Importance: high `secret.manager.provider.integration.id` : Select an existing provider integration that has access to your secret manager.
* Type: string * Importance: high ### 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, whenever possible.
* Type: string * Valid Values: SERVICE_ACCOUNT, KAFKA_API_KEY * 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 ### How should we connect to your database? `mongodb.connection.string` : Enter the MongoDB connection string in the format `mongodb://host:port` or `mongodb+srv://cluster.example.com`. Do not include credentials here. Use the specific user, password, or provider integration fields instead.
* Type: string * Importance: high `mongodb.user` : Enter a MongoDB username with `readAnyDatabase` role and `changeStream` privileges.
For sharded clusters, the user also requires `read` access to the `config` and `local` databases.
If enabling incremental snapshots, ensure the user has write access to the signal data collection.
* Type: string * Importance: high `mongodb.password` : Enter the password for the specified MongoDB database user.
* Type: password * Importance: high `mongodb.ssl.enabled` : Set to `true` to enable an SSL/TLS encrypted connection to MongoDB. The default is `false`.
* Type: boolean * Default: false * Importance: high `mongodb.ssl.truststore` : Provide the trust store file containing trusted certificates in JKS or PKCS12 format. This is required when TLS is enabled. When using Confluent Rest API or Confluent CLI, encode the file in base64 and use this format: `data:application/octet-stream;base64,`.
* Type: password * Importance: medium `mongodb.ssl.truststore.password` : Enter the password required to access the SSL truststore.
* Type: password * Importance: medium `mongodb.ssl.invalid.hostname.allowed` : Determines whether to disable SSL hostname verification.
Set to `true` for development or testing only.
Set to `false` (default) in production to ensure secure hostname validation.
Setting this to `true` is not secure in production environments and may violate your organization’s security policies. Confluent Cloud connectors use TLS by default with strict hostname verification.
* Type: boolean * Default: false * Importance: medium `mongodb.authsource` : Specify the database containing user credentials for authentication. This defaults to `admin`.
* Type: string * Default: admin * Importance: medium ### Output messages `output.data.format` : Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, 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: JSON * 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: JSON * Valid Values: AVRO, JSON, JSON_SR, PROTOBUF, STRING * Importance: high `after.state.only` : Determines whether to emit only the document state after a change.
When `true`, emits only the document state after the change.
When `false` (default), emits the full Debezium envelope with operation metadata.
* Type: boolean * Default: false * Importance: low `tombstones.on.delete` : Determines if the connector emits a tombstone event after a delete event.
If set to `true` (Default), the connector emits both the delete event and a tombstone for log compaction.
If set to `false`, the connector emits only the delete event.
* Type: boolean * Default: true * Importance: medium ### How should we name your topic(s)? `topic.prefix` : * Type: string * Valid Values: Must match the regex `^[a-zA-Z0-9._\-]+$` * Importance: high ### How should we configure the topic(s)? `topic.creation.topic_prefix_match.partitions` : Number of partitions for Kafka topics auto-created by the connector for topics whose name starts with `topic.prefix.`. Kafka preserves message ordering only within a partition. The connector keys each change event by the changed record’s primary key, and Kafka routes all events with the same key to the same partition - so events sharing a key stay in order, while events with different keys may be spread across partitions and lose their relative order. Tables that have no primary key produce unkeyed events, which Kafka distributes across all partitions, so any value above 1 removes ordering guarantees for those tables entirely. Keep this at 1 (the default) if you need all change events in a topic delivered in strict order.
* Type: int * Default: 1 * Valid Values: [1,…] * Importance: high `topic.creation.topic_prefix_match.cleanup.policy` : Cleanup policy applied to Kafka topics auto-created by the connector for topics whose name starts with `topic.prefix.`. `compact` retains only the latest value per key (typical for change-data-capture topics); `delete` ages records out based on retention settings.
* Type: string * Default: delete * Valid Values: compact, compact,delete, delete * Importance: high ### Storage `topic.creation.topic_prefix_match.retention.ms` : Time-based retention, in milliseconds, applied to Kafka topics auto-created by the connector for topics whose name starts with `topic.prefix.`. Use `-1` for infinite retention.
* Type: long * Default: 604800000 (7 days) * Valid Values: [-1,…] * Importance: high `topic.creation.topic_prefix_match.retention.bytes` : Size-based retention, in bytes, applied to Kafka topics auto-created by the connector for topics whose name starts with `topic.prefix.`. Use `-1` for unlimited size.
* Type: long * Default: -1 * Valid Values: [-1,…] * Importance: high ### Database config `database.include.list` : Provide a comma-separated list of databases to monitor.
Supports regular expressions when `filters.match.mode` is `regex`.
If empty, includes all databases in the `capture.scope`.
Do not use this with `database.exclude.list`.
* Type: list * Importance: high `database.exclude.list` : Provide a comma-separated list of database names to exclude.
Supports regular expressions when `filters.match.mode` is `regex`.
Do not use this with `database.include.list`.
* Type: list * Importance: high `collection.include.list` : Provide a comma-separated list of fully-qualified collections (`database.collection`) to capture.
Supports regular expressions through `filters.match.mode`.
Do not use this with `collection.exclude.list`.
* Type: list * Importance: high `collection.exclude.list` : Provide a comma-separated list of fully-qualified collections (`database.collection`) to exclude from data capture.
* Type: list * Importance: high `field.exclude.list` : Provide a comma-separated list of fully-qualified field names (`database.collection.field`) to exclude from data capture.
* Type: list * Importance: medium `field.renames` : Provide a comma-separated list of field rename mappings in the format `database.collection.oldName:newName`.
* Type: string * Importance: medium `filters.match.mode` : Determines the matching logic for include and exclude filters.
`regex` enables regular expression matching.
`literal` enables exact string matching.
* Type: string * Default: regex * Valid Values: literal, regex * Importance: medium ### Snapshot Configs `snapshot.mode` : Set the behaviour for initial data capture.
`initial` performs a snapshot only on the first start.
`no_data` skips snapshot.
`when_needed` performs a snapshot only if offsets are missing or invalid.
`initial_only` performs a snapshot and then stops the connector.
* Type: string * Default: initial * Valid Values: initial, initial_only, no_data, when_needed * Importance: high `snapshot.include.collection.list` : Provide a comma-separated list of collections to snapshot.
This must be a subset of `collection.include.list`.
* Type: list * Importance: medium `snapshot.delay.ms` : Set the interval in milliseconds to wait before starting a snapshot after the connector starts. Default is `0ms`.
* Type: long * Default: 0 * Valid Values: [0,…] * Importance: low ### Streaming Configs `streaming.delay.ms` : Set the delay in milliseconds between completing a snapshot and starting streaming. Default is `60000` (1 minute). This buffer ensures offsets are committed and prevents duplicate snapshots on connector restart.
* Type: long * Default: 60000 (1 minute) * Valid Values: [0,…] * Importance: low ### Signal Configs `signal.enabled.channels` : Provide a list of signalling channels to enable:
`source` (default): Reads from the database collection.
`kafka`: Consumes from a Kafka topic.
Note: `source` is required when using `kafka`.
* Type: list * Importance: medium `signal.data.collection` : Specify the fully-qualified collection (`database.collection`) that stores control signals for snapshot operations. This setting is required when signal channels are configured. The connector monitors this collection for signal documents to trigger snapshot actions. The connector needs to have `write` permissions on this collection.
* Type: string * Importance: medium `signal.kafka.topic` : Set the name of the Kafka topic the connector monitors for ad-hoc signals through the Confluent Cloud CLI. Note that signal.kafka.topic must have exactly 1 partition as the connector’s signal consumer reads only from partition-0. Any signal messages routed to other partitions are silently ignored in a multi-partition topic.
* Type: string * Importance: low ### Incremental Snapshot Configs `incremental.snapshot.chunk.size` : Set the maximum number of documents fetched per incremental snapshot chunk. Tune this based on available heap memory. Larger values improve throughput by reducing query overhead but increase memory consumption.
* Type: int * Default: 1024 * Valid Values: [1,…,1024] * Importance: medium `incremental.snapshot.watermarking.strategy` : Set the strategy for watermarking during incremental snapshots.
`INSERT_INSERT` (Default) writes both open and close signals.
`INSERT_DELETE` writes the open signal and deletes it upon closing.
* Type: string * Default: INSERT_INSERT * Importance: low ### Connector config `capture.mode` : Determines the mechanism for capturing document changes.
`change_streams` captures only modified fields.
`change_streams_update_full` captures the full document state (recommended).
`change_streams_with_pre_image` includes the `before` state (requires MongoDB 6.0 or later versions).
`change_streams_update_full_with_pre_image` combines full updates and pre-images.
* Type: string * Default: change_streams_update_full * Valid Values: change_streams, change_streams_update_full, change_streams_update_full_with_pre_image, change_streams_with_pre_image * Importance: high `skipped.operations` : Comma-separated list of operations to skip. Supported options are:
`c` (insert)
`u` (update)
`d` (delete)
`none` (no operations skipped).
* Type: list * Default: none * Importance: low `capture.scope` : Defines the boundary for data capture.
`deployment` captures from the entire cluster or replica set.
`database` limits capture to the database in `capture.target`.
`collection` limits capture to the collection in `capture.target`.
* Type: string * Default: deployment * Valid Values: collection, database, deployment * Importance: medium `capture.target` : Specifies the target name when `capture.scope` is `database` or `collection`.
Use the database name for `scope=database` or `database.collection` for `scope=collection`.
The connector ignores this setting if the scope is `deployment`.
* Type: string * Importance: high `capture.mode.full.update.type` : Set the method for obtaining the full document for updates. `lookup` performs a separate query, and `post_image` uses MongoDB post-images (requires MongoDB 6.0 or later versions).
* Type: string * Default: lookup * Valid Values: lookup, post_image * Importance: medium `field.name.adjustment.mode` : Specifies how to adjust field names for converter compatibility.
`none` applies no adjustment.
`avro` replaces invalid characters with underscores.
`avro_unicode` replaces invalid characters with unicode sequences.
* Type: string * Default: none * Valid Values: avro, avro_unicode, none * Importance: medium `schema.name.adjustment.mode` : Specifies how to adjust schema names for converter compatibility.
`none`: Applies no adjustment.
`avro`: Replaces invalid characters with underscores.
`avro_unicode`: Replaces invalid characters with unicode sequences.
Note that \_ is an escape sequence like backslash in Java.
* Type: string * Default: none * Valid Values: avro, avro_unicode, none * Importance: medium `heartbeat.interval.ms` : Set the frequency in milliseconds for sending heartbeat messages to Kafka. Set to `0` (Default) to disable. Heartbeats monitor connector health and can reduce the volume of re-sent events upon restart.
* Type: int * Default: 0 * Valid Values: [0,…] * Importance: low `max.batch.size` : Set the number of events processed per batch. Choose a value between `1` and `5000`. Defaults to `2048`.
* Type: int * Default: 2048 * Valid Values: [1,…,5000] * Importance: low ### 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 `key.converter.reference.subject.name.strategy` : Set the subject reference name strategy for the key. Supported options are `DefaultReferenceSubjectNameStrategy` (Default), and `QualifiedReferenceSubjectNameStrategy`.
These options are selectable only for the `PROTOBUF` format.
* Type: string * Default: DefaultReferenceSubjectNameStrategy * Importance: high ### Number of tasks for this connector `tasks.max` : The maximum number of tasks for the connector. Only one task is supported for this 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](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.schema.id.serializer` : The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer * Importance: low `key.converter.key.subject.name.strategy` : How to construct the subject name for key schema registration.
* Type: string * Default: TopicNameStrategy * 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.schema.id.serializer` : The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer * 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 `provide.transaction.metadata` : Determines if the connector generates transaction boundary events and enriches change event envelopes with transaction metadata. When enabled, the connector creates a dedicated transaction metadata topic. Its name starts with your topic prefix, so it uses the same partition, retention, and cleanup settings as your other topics with that prefix.
* Type: boolean * Default: false * Importance: low `topic.transaction` : Set the topic name for transaction metadata. The final name follows the pattern `.`. Defaults to `{{.logicalClusterId}}.transaction`. Because this topic’s name always starts with your topic prefix, it uses the same partition, retention, and cleanup settings as your other topics with that prefix.
* Type: string * Default: {{.logicalClusterId}}.transaction * Importance: low `topic.heartbeat.prefix` : Specifies the prefix for the heartbeat topic where the connector sends periodic heartbeat messages.
Pattern: ..
Defaults to \_\_debezium-heartbeat-{{.logicalClusterId}}. By default the heartbeat topic does not start with your topic prefix, so it is created with a single partition. If you change this prefix so that the heartbeat topic name starts with your topic prefix followed by a period, it instead uses the same partition, retention, and cleanup settings as your other topics with that prefix. Keep the default unless you have a specific reason to change it.
* Type: string * Default: \_\_debezium-heartbeat-{{.logicalClusterId}} * Importance: low `cursor.pipeline` : Define a MongoDB aggregation pipeline as a JSON array to filter change stream events at the database level.
* Type: string * Importance: medium `cursor.pipeline.order` : Set the execution order for pipeline stages.
`internal_first` runs connector stages before user stages.
`user_first` runs user stages before connector stages.
`user_only` runs only user stages and bypasses connector stages.
* Type: string * Default: internal_first * Valid Values: internal_first, user_first, user_only * Importance: low `cursor.oversize.handling.mode` : Determines the strategy for handling BSON documents that exceed size limits.
`fail` stops the connector.
`skip` ignores the document.
`split` fragments large events (requires MongoDB 6.0.9 or later versions).
* Type: string * Default: fail * Valid Values: fail, skip, split * Importance: medium `cursor.oversize.skip.threshold` : Provide the maximum document size in bytes when `cursor.oversize.handling.mode` is `skip`. Documents exceeding this size are skipped. Must be greater than 0.
* Type: int * Default: 0 * Valid Values: [0,…] * Importance: low `poll.interval.ms` : Set the time in milliseconds to wait for new change events when no data is returned. Default is `500ms`.
* Type: long * Default: 500 * Valid Values: [200,…] * Importance: low `mongodb.heartbeat.frequency.ms` : Set the interval in milliseconds for the cluster monitor to detect membership changes in the replica set. Minimum value must be 500ms.
* Type: int * Default: 10000 (10 seconds) * Valid Values: [500,…] * Importance: low `notification.enabled.channels` : Provide a comma-separated list of enabled channels. `log` logs notifications, and `sink` sends notifications to the topic in `notification.sink.topic.name`.
* Type: list * Importance: low `notification.sink.topic.name` : Set the Kafka topic name for notifications. This is required in case `sink` is in the list of enabled channels. If you set this name so that it starts with your topic prefix followed by a period, the topic uses the same partition, retention, and cleanup settings as your other topics with that prefix; otherwise it is created with a single partition.
* Type: string * 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](/platform/current/tutorials/examples/cloud-etl/docs/index.html). This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud. [](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)