# MongoDB Atlas Sink Connector for Confluent Cloud The fully managed MongoDB Atlas Sink connector for Confluent Cloud maps and persists events from Apache Kafka® topics directly to a MongoDB Atlas database collection. The connector supports Avro, JSON Schema, Protobuf, JSON (schemaless), String, or BSON data from Apache Kafka® topics. The connector ingests events from Kafka topics directly into a MongoDB Atlas database, exposing the data to services for querying, enrichment, and analytics. #### NOTE * This Quick Start is for the fully managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see [MongoDB Kafka Connector](https://docs.mongodb.com/kafka-connector/current/) documentation. * The fully managed MongoDB Atlas Sink connector for Confluent Cloud connects to resources in the same region and cloud provider as your Confluent Cloud cluster. If your MongoDB Atlas instance is in a different region or cloud provider than your Confluent Cloud cluster, contact [Confluent Support](https://support.confluent.io/hc/en-us) to enable cross-region or cross-cloud connectivity before you configure the connector. * 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 Atlas Sink connector supports both MongoDB Atlas and self-managed MongoDB databases. The connector provides the following features: * **Collections:** Collections can be auto-created based on topic names. * **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](#cc-mongo-db-sink-setup-connection). * **Input data formats:** The connector supports Avro, JSON Schema, Protobuf, JSON (schemaless), String, or BSON input data formats. [Schema Registry](../../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). * **Select configuration properties:** - `"max.num.retries"`: How often retries should be attempted on write errors. - `"max.batch.size"`: The maximum number of sink records to batch together for processing. - `"delete.on.null.values"`: Whether the connector should delete documents with matching key values when the value is null. - `"doc.id.strategy"`: The strategy to generate a unique document ID (`_id`). - `"write.strategy"`: Defines the behavior of bulk write operations made on a MongoDB collection. See [Configuration Properties](#cc-mongodb-sink-config-properties) for all property values and definitions. * **Client-side encryption (CSFLE and CSPE) support**: The connector supports CSFLE and CSPE for sensitive data. For more information about CSFLE or CSPE setup, see the [connector configuration](#cc-mongo-db-sink-setup-connection). * **Secret manager integration**: The connector supports secret manager integration. For `SCRAM-SHA-256` (username and password) authentication, the connector can retrieve the following configurations from an integrated secret manager at runtime as needed. | **Secret manager managed configuration** | **Type** | |--------------------------------------------|------------| | `connection.host` | `STRING` | | `connection.user` | `STRING` | | `connection.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. ## Limitations Be sure to review the following information. * For connector limitations, see [MongoDB Atlas Sink Connector](../limits.md#cc-mongo-db-sink-limits) limitations. * If you plan to use one or more Single Message Transformations (SMTs), see [SMT Limitations](../single-message-transforms.md#cc-single-message-transforms-limitations). ## Quick Start Use this quick start to get up and running with the Confluent Cloud MongoDB Atlas sink connector. The quick start provides the basics of selecting the connector and configuring it to consume data from Kafka and persist the data to a MongoDB database. 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) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). - Access to a MongoDB database. - The MongoDB database service endpoint and the Kafka cluster must be in the same region. - 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. - 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). - If you have a VPC-peered cluster in Confluent Cloud, consider configuring a [PrivateLink Connection](https://docs.atlas.mongodb.com/security-private-endpoint/#configure-an-service-private-endpoint) between MongoDB Atlas and 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. ### Adding an IP Whitelist Entry #### IMPORTANT * 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). By default, MongoDB Atlas does not allow external network connections from the Internet. To allow external connections, you can add a specific IP or a CIDR IP range using the **IP Whitelist** entry dialog box under the **Network Access** menu in MongoDB. In order for Confluent Cloud to connect to MongoDB Atlas, you need to specify the public IP address of your Confluent Cloud cluster. Add all of the Confluent Cloud egress IP addresses to the whitelist entry to your MongoDB Atlas cluster. ![MongoDB IP Whitelist Entry](images/ccloud-mongodb-ip-whitelist.png) ### 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 Atlas Sink** connector card. ![MongoDB Atlas Sink Connector Card](images/ccloud-mongodb-sink-icon.png) #### Step 4: Enter the connector details #### NOTE * Ensure you have all your [prerequisites](#cc-mongo-db-sink-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add MongoDB Atlas Sink Connector** screen, complete the following: ### Topic selection If you’ve already populated your Kafka topics, select the topics you want to connect from the **Topics** list. To create a new topic, click **+Add new topic**. ### 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: **MongoDB instance type** - **MongoDB instance type**: Specify the MongoDB deployment type. Use **MONGODB_ATLAS** for cloud hosted Atlas clusters or **MONGODB_SELF_MANAGED** for self hosted MongoDB instances. **MongoDB authentication mechanism** - **Authentication mechanism**: Choose an authentication mechanism for MongoDB. Use **SCRAM-SHA-256** for username or password authentication. Use **MONGODB-X509** for certificate-based authentication. For **MONGODB-X509**, you must configure the SSL keystore properties. **How should we connect to your MongoDB database?** - **Use secret manager**: Fetch sensitive configuration values from a secret manager. **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 secret manager. **MongoDB credentials** - **Connection host**: The MongoDB host with connection string options. Use a hostname address and not a full URL. For example, use `cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary` for **MONGODB_ATLAS** and `54.190.171.123:27017/?authSource=admin` for **MONGODB_SELF_MANAGED**. #### NOTE You don’t need to manually add the connection string parameters `authMechanism=MONGODB-X509&authSource=$external` as part of the host. The connector automatically includes the parameter when you select `MONGODB-X.509` as the authentication mechanism. - **Connection user**: The MongoDB Atlas connection user. - **Connection password**: The MongoDB Atlas connection password. When entering the password, make sure that any special characters are URL encoded. **MongoDB Database Details** - **Database name**: The MongoDB Atlas database name. - **Collection name**: The collection name to write to. If the connector is sinking data from multiple topics, this is the default collection the topics are mapped to. **SSL Configuration** - **SSL keystore file**: Upload the SSL keystore file containing the server certificate and enter the SSL keystore password used to access the keystore. - **SSL keystore password**: Password used to access the keystore. - **SSL truststore file**: Upload the SSL truststore file containing a server CA certificate and enter the SSL truststore password used to access the truststore. - **SSL truststore password**: Password used to access the truststore. 2. Click **Continue**. ### Configuration #### NOTE See [Configuration Properties](#cc-mongodb-sink-config-properties) for all property values and definitions. - **Input Kafka record value format**: Sets the input 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. **Data decryption** - Enable **Client-Side Field Level Encryption** for data decryption. Specify a **Service Account** to access the Schema Registry and associated encryption rules or keys with that schema. Select the connector behavior (`ERROR` or `NONE`) on data decryption failure. If set to `ERROR`, the connector fails and writes the encrypted data in the DLQ. If set to `NONE`, the connector writes the encrypted data in the target system without decryption. For more information on CSFLE or CSPE setup, see [Manage encryption for connectors](../csfle.md#connect-csfle). ### **Show advanced configurations** - **Schema context**: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the **Default** context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a **Source** connector uses only that schema context to register a schema and a **Sink** connector uses only that schema context to read from. For more information about setting up a schema context, see [What are schema contexts and when should you use them?](../../sr/faqs-cc.md#faq-schema-contexts). - **Input Kafka record key format**: Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF. - **Post Processor Chain**: A comma separated list of post processor classes to process the data before saving to MongoDB. - **Field Renamer Mapping**: An inline JSON array with objects describing field name mappings. Example: `[{\"oldName\":\"key.fieldA\",\"newName\":\"field1\"},{\"oldName\":\"value.xyz\",\"newName\":\"abc\"}]`. - **Topic override map**: A JSON map to override sink connector properties for specific topics. Specify the map as `{".": ""}`. For example, `{"orders.collection": "orders_collection", "orders.database": "orders_db"}` routes the *orders* topic to the *orders_collection* in the *orders_db* database. Supported properties are `collection`, `database`, and other topic-level sink configurations. **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 Schema ID Deserializer**: Sets the class name of the schema ID deserializer for values. The deserializer reads schema IDs from message headers. - **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`. - **Schema ID For Value Converter**: Sets the schema ID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema ID for deserializing message values. This property is applicable only when `value.converter.value.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **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. - **Key Converter Schema ID Deserializer**: Sets the class name of the schema ID deserializer for keys. The deserializer reads schema IDs from message headers. - **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. - **Schema GUID For Key Converter**: Sets the schema GUID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema GUID for deserializing message keys. This property is applicable only when `key.converter.key.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **Schema GUID For Value Converter**: Sets the schema GUID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema GUID for deserializing message values. This property is applicable only when `value.converter.value.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **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. - **Schema ID For Key Converter**: Sets the schema ID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema ID for deserializing message keys. This property is applicable only when `key.converter.key.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. **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. **Consumer configuration** - **Max poll interval(ms)**: Sets the maximum delay between subsequent consume requests to Kafka. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 300,000 milliseconds (5 minutes). - **Max poll records**: Sets the maximum number of records to consume from Kafka in a single request. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 500 records. **Input messages** - **Change Data Capture handler**: Sets the class name of the CDC handler to use for processing. You can capture CDC events with this connector and perform corresponding insert, update, and delete operations to a destination MongoDB cluster. Valid options are `None`, `MongoDbChangeStreamHandler`, `DebeziumMongoDbHandler`, `DebeziumMySqlHandler`, `DebeziumPostgresHandler`, or `QlikRdbmsHandler`. If not used, this property defaults to `None`. For more information, see [mongodb-sink-cdc](https://docs.mongodb.com/kafka-connector/current/kafka-sink-cdc/#kafka-sink-change-data-capture). **Writes** - **Delete on null values**: Select whether or not the connector deletes documents with matching key values when the value is null. The default is false. - **Write Model Strategy**: The class that specifies the `WriteModel` to use for bulk writes. Defaults to `DefaultWriteModelStrategy`. Valid entries are `DefaultWriteModelStrategy`, `ReplaceOneDefaultStrategy`, `InsertOneDefaultStrategy`, `ReplaceOneBusinessKeyStrategy`, `DeleteOneDefaultStrategy`, `UpdateOneTimestampsStrategy`, `UpdateOneBusinessKeyTimestampStrategy`, or `UpdateOneDefaultStrategy`. For time-series collections, the `DefaultWriteModelStrategy` will internally default to `InsertOneDefaultStrategy`. For normal collections, it defaults to `ReplaceOneDefaultStrategy`. For detailed information about each write strategy, see [Strategies](https://www.mongodb.com/docs/kafka-connector/master/sink-connector/configuration-properties/write-strategies/#strategies). - **Max batch size**: Enter the maximum number of records to batch together for processing. The default is `0` (uses the server default setting). - **Use ordered bulk writes**: When batch processing is used, this property sets whether the connector writes the batches using ordered bulk writes. Defaults to `true`. - **Rate limiting timeout**: After a rate limit is reached, this sets how long in milliseconds (ms) the connector waits before continuing to process data. Defaults to `0`. - **Rate limiting batch number**: The number of processed batches that trigger a rate limit. Defaults to `0` (that is, no rate limiting). - **Delete Write Model Strategy**: The class that handles how to build the delete write models for the sink documents. **Connection details** - **Max number of retries**: Enter the maximum number of retries on a write error. The default value is 3 retries. - **Retry defer timeout (ms)**: Enter value in milliseconds (ms) that a retry gets deferred. The default is 5000 ms (5 seconds). **ID strategies** - **Document ID strategy**: Select the strategy to generate a unique document ID `_id`. To delete a document when the value is null, this has to be set to `FullKeyStrategy`, `PartialKeyStrategy`, or `ProvidedInKeyStrategy`. The default is `BsonOidStrategy`. For more information, see [DocumentIdAdder](https://docs.mongodb.com/kafka-connector/current/kafka-sink-postprocessors#documentidadder). - **Document ID strategy overwrite existing**: Whether the connector should overwrite existing values in the `_id` field when the strategy defined in `doc.id.strategy` is applied. - **Document ID strategy UUID format**: The BSON output format when using `UuidStrategy`. Options are `String` or `Binary`. - **Document ID strategy key projection type**: For use with the `PartialKeyStrategy`. Allows custom key fields to be projected for the ID strategy. Use either `AllowList` or `BlockList`. - **Document ID strategy key projection list**: For use with the `PartialKeyStrategy`. Allows custom key fields to be projected for the ID strategy. A comma-separated list of fields names for key projection. - **Document ID strategy value projection type**: For use with the `PartialValueStrategy`. Allows custom value fields to be projected for the ID strategy. Use either `AllowList` or `BlockList`. - **Document ID strategy value projection list**: For use with the `PartialValueStrategy`. Allows custom value fields to be projected for the ID strategy. A comma-separated list of field names for value projection. **Time Series configuration** - **Timefield**: The name of the top-level time field that contains the date in each time-series document. Setting this config will create a time-series collection where each document will have a BSON date value for the time field. Time-series collections were introduced in MongoDB v5.0, which is only available for dedicated clusters in MongoDB Atlas. For more information, see [Time Series Properties](https://www.mongodb.com/docs/kafka-connector/current/sink-connector/configuration-properties/time-series/). - **Auto Conversion**: Whether to convert the data in the time field to BSON date format. Supported formats include integer, long and string. - **Auto Convert Date Format**: The string pattern to convert the source data from format to convert the source data from. The setting expects the string representation to contain both date and time information and uses the Java `DateTimeFormatter.ofPattern` (pattern, locale) API for the conversion. If the string only contains date information, then the time since epoch is from the start of that day. If a string representation does not contain time-zone offset, then the setting interprets the extracted date and time as UTC. - **Locale Language Tag**: The `DateTimeFormatter`’s locale language tag to use with the date pattern. - **Metafield**: The name of the top-level field that contains metadata in each time-series document. The metadata in the specified field should be data that is used to label a unique series of documents. The field can be of any type except array. - **Expire After Seconds**: The amount of seconds the data remains in MongoDB before MongoDB deletes it. Omitting this field means data will not be deleted automatically. - **Granularity**: The expected interval between subsequent measurements for a time-series. Set this to `None` or leave it blank to disable time-series collection creation. **Server API** - **Server API version**: The server API version to use. Disabled by default. - **Deprecation errors**: Sets whether the connector requires use of deprecated server APIs to be reported as errors. - **Strict**: Sets whether the application requires strict server API version enforcement. **Namespace mapping** - **Namespace mapper class**: The class that determines the namespace to write the sink data to. By default, this is based on the ‘database’ configuration and either the topic name or the ‘collection’ configuration. - **Key field for destination database name**: The key field to use as the destination database name. - **Key field for destination collection name**: The key field to use as the destination collection name. - **Value field for destination database name**: The value field to use as the destination database name. - **Value field for destination collection name**: The value field to use as the destination collection name. - **Mapped field error**: Whether to throw an error if the mapped field is missing or invalid. Defaults to false. **Error handling Mongo** - **Error tolerance**: Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework’s. **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). - Click **Continue**. ### Sizing Based on the number of topic partitions you select, you will be provided with a recommended number of tasks. One task can handle up to 100 partitions. 1. To change the number of recommended tasks, enter the number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use in the **Tasks** field. 2. Click **Continue**. ### Review and launch Review the configuration summary and verify the following: 1. Verify the connection details and click **Launch**. ![Launch the connector](images/ccloud-mongodb-sink-launch-connector.png) The status for the connector should go from **Provisioning** to **Running**. It may take a few minutes. ![Check the connector status](images/ccloud-mongodb-sink-status.png) #### Step 5: Check MongoDB After the connector is running, verify that messages are populating your MongoDB database. ### 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](#cc-mongo-db-sink-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 example shows the required connector properties. ```json { "connector.class": "MongoDbAtlasSink", "name": "confluent-mongodb-sink", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "", "input.data.format" : "JSON", "connection.host": "", "connection.user": "", "connection.password": "", "topics": "", "max.num.retries": "3", "retries.defer.timeout": "5000", "max.batch.size": "0", "database": "", "collection": "", "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](../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 ``` * `"input.data.format"`: Sets the input Kafka record value format (data coming from the Kafka topic). 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). * `"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](https://www.mongodb.com/docs/manual/reference/connection-string-options/#std-label-connections-connection-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`. * `"collection"`: The MongoDB collection name. For multiple topics, this is the default collection the topics are mapped to. The following are optional (with the exception of the number of tasks). * `"max.num.retries"`: How often retries should be attempted on write errors. If not used, this property defaults to 3. * `"retries.defer.timeout"`: How long (in milliseconds) a retry should get deferred. If not used, the default is 5000 ms. * `"max.batch.size"`: The maximum number of sink records to batch together for processing. If not used, this property defaults to 0. * `"delete.on.null.values"`: Whether the connector should delete documents with matching key values, when the value is null. If not used, this property defaults to `false`. * `"doc.id.strategy"`: Sets the strategy to generate a unique document ID `(_id)`. Enter the strategy to **generate a unique document ID (_id)**. Valid entries are `BsonOidStrategy`, `KafkaMetaDataStrategy`, `FullKeyStrategy`, `PartialKeyStrategy`, `PartialValueStrategy`, `ProvidedInKeyStrategy`, `ProvidedInValueStrategy`, or `UuidStrategy`. To delete the document when the value is null, you must set the strategy to `FullKeyStrategy`, `PartialKeyStrategy`, or `ProvidedInKeyStrategy`. The default value is `BsonOidStrategy`. For more information, see [DocumentIdAdder](https://docs.mongodb.com/kafka-connector/current/kafka-sink-postprocessors#documentidadder). * Depending on the selected strategy, add the appropriate **Document ID strategy projection list**: - `"key.projection.type"`: For use with `PartialKeyStrategy`. Use either `allowlist` or `blocklist` to allow or block the custom key fields to be projected for ID strategy. If not used, this property defaults to `none`. - `"key.projection.list"`: For use with `PartialKeyStrategy`. A comma-separated list of key fields to be projected for ID strategy. - `"value.projection.type"`: For use with `PartialValueStrategy`. Use either `allowlist` or `blocklist` to allow or block the custom value fields to be projected for ID strategy. If not used, this property defaults to `none`. - `"value.projection.list"`: For use with `PartialValueStrategy`. A comma-separated list of value fields to be projected for ID strategy. * `"write.strategy"`: Sets the write model for bulk write operations. Valid entries are `DefaultWriteModelStrategy`, `ReplaceOneDefaultStrategy`, `InsertOneDefaultStrategy`, `ReplaceOneBusinessKeyStrategy`, `DeleteOneDefaultStrategy`, `UpdateOneTimestampsStrategy`, `UpdateOneBusinessKeyTimestampStrategy`, or `UpdateOneDefaultStrategy`. If not used, this property defaults to `DefaultWriteModelStrategy`. For time-series collections, the `DefaultWriteModelStrategy` will internally default to `InsertOneDefaultStrategy`. For normal collections, it defaults to `ReplaceOneDefaultStrategy`. For detailed information about each write strategy, see [Strategies](https://www.mongodb.com/docs/kafka-connector/master/sink-connector/configuration-properties/write-strategies/#strategies). * `"cdc.handler"`: Sets the class name of CDC handler to use for processing. You can capture CDC events with the MongoDB Kafka Sink connector and perform corresponding insert, update, and delete operations to a destination MongoDB cluster. Valid entries are `None`, `MongoDbChangeStreamHandler`, `DebeziumMongoDbHandler`, `DebeziumMySqlHandler`, `DebeziumPostgresHandler`, or `QlikRdbmsHandler`. If not used, this property defaults to `None`. For more information, see [mongodb-sink-cdc](https://docs.mongodb.com/kafka-connector/current/kafka-sink-cdc/#kafka-sink-change-data-capture). * `"timeseries.timefield"`: Sets the name of the top-level time field that contains the date in each time-series document. Setting this property will create a time-series collection where each document will have a BSON date as the value for the time field. Time-series collections were introduced in MongoDB v5.0, which is only available for dedicated clusters in MongoDB Atlas. * `"timeseries.timefield.auto.convert"`: Whether to convert the data in the time field to BSON date format. Supported formats for data include integer, long and string. If not used, this property defaults to `false`. * `"timeseries.timefield.auto.convert.date.format"`: Sets the DateTimeFormatter format to convert the source data from. The setting expects the string representation to contain both date and time information and uses the Java DateTimeFormatter.ofPattern(pattern, locale) API for the conversion. If the string only contains date information, then the time since epoch is from the start of that day. If a string representation does not contain time-zone offset, then the setting interprets the extracted date and time as UTC. If not used, this property defaults to `yyyy-MM-dd[['T'][ ]][HH:mm:ss[[.][SSSSSS][SSS]][ ]VV[ ]'['VV']'][HH:mm:ss[[.][SSSSSS][SSS]][ ]X][HH:mm:ss[[.][SSSSSS][SSS]]]`. * `"timeseries.timefield.auto.convert.locale.language.tag"`: Sets the DateTimeFormatter locale language tag to use with the date pattern. See [Language tags in HTML and XML](https://www.w3.org/International/articles/language-tags/) for more information on constructing tags. If not used, this property defaults to `en`. * `"timeseries.metafield"`: Sets the name of the top-level field that contains metadata in each time-series document. The metadata in the specified field should be data that is used to label a unique series of documents. The field can be of any type except array. * `"timeseries.expire.after.seconds"`: Sets the number of seconds after which the document expires. MongoDB deletes expired documents automatically. If not used, this property default to `0`, which means data will not be deleted automatically. * `"ts.granularity"`: Sets the interval granularity for subsequent measurements for a time-series. Valid entries are `None`, `seconds`, `minutes`, or `hours`. If not used, this property defaults to `None`. For normal collections, `None` is the only applicable value. For time-series collections, all entries are applicable and `None` internally defaults to `seconds`. * Enter the number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector. Refer to Confluent Cloud [connector limitations](../limits.md#cc-mongo-db-sink-limits) for additional information. #### 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. * `csfle.onFailure`: Configures the connector behavior (`ERROR` or `NONE`) on data decryption failure. If set to `ERROR`, the connector fails and writes the encrypted data in the DLQ. If set to `NONE`, the connector writes the encrypted data in the target system without decryption. When using CSFLE or CSPE with connectors that route failed messages to a Dead Letter Queue (DLQ), be aware that data sent to the DLQ is written in unencrypted plaintext. This poses a significant security risk as sensitive data that should be encrypted may be exposed in the DLQ. Do not use DLQ with CSFLE or CSPE in the current version. If you need error handling for CSFLE- or CSPE-enabled data, use alternative approaches such as: * Setting the connector behavior to `ERROR` to throw exceptions instead of routing to DLQ * Implementing custom error handling in your applications * Using `NONE` to pass encrypted data through without decryption 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. See [Configuration Properties](#cc-mongodb-sink-config-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: ```none confluent connect cluster create --config-file .json ``` For example: ```none confluent connect cluster create --config-file mongo-db-sink.json ``` Example output: ```none Created connector confluent-mongodb-sink 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 | confluent-mongodb-sink | RUNNING | sink ``` #### Step 6: Check MongoDB After the connector is running, verify that records are populating your MongoDB database. ## 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](/platform/current/connect/kafka_connectors.html). ### 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 ### 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 ### Input messages `input.data.format` : Sets the input 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: JSON * Importance: high `input.key.format` : Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. 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, BYTES, JSON, JSON_SR, PROTOBUF, STRING * Importance: high `cdc.handler` : The class name of the CDC handler to use for processing. You can capture CDC events with the MongoDB Kafka sink connector and perform corresponding insert, update, and delete operations to a destination MongoDB cluster.
* Type: string * Default: None * Importance: low ### Writes `delete.on.null.values` : Whether or not the connector should try to delete documents based on key when value is null.
* Type: boolean * Default: false * Importance: low `max.batch.size` : The maximum number of sink records to possibly batch together for processing.
* Type: int * Default: 0 * Valid Values: [0,…] * Importance: low `bulk.write.ordered` : Whether the batches controlled by ‘max.batch.size’ must be written via ordered bulk writes.
* Type: boolean * Default: true * Importance: low `rate.limiting.timeout` : How long in ms processing should wait before continuing after triggering a rate limit.
* Type: int * Default: 0 * Importance: low `rate.limiting.every.n` : The number of processed batches that will trigger rate limiting. The default value of 0 sets no rate limiting.
* Type: int * Default: 0 * Importance: low `write.strategy` : The class that specifies the WriteModel to use for bulk writes.
* Type: string * Default: DefaultWriteModelStrategy * Importance: low `delete.write.strategy` : The class that handles how to build the delete write models for the sink documents.
* Type: string * Default: DeleteOneDefaultStrategy * Importance: low `topic.override.map` : A JSON map to override sink connector properties for specific topics. Specify the map as `{".": ""}`. For example, `{"orders.collection": "orders_collection", "orders.database": "orders_db"}` routes the *orders* topic to the *orders_collection* in the *orders_db* database. Supported properties are `collection`, `database`, and other topic-level sink configurations.
* Type: string * Default: {} * Importance: low ### 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 ### Which topics do you want to get data from? `topics.regex` : A regular expression that matches the names of the topics to consume from. This is useful when you want to consume from multiple topics that match a certain pattern without having to list them all individually.
* Type: string * Importance: low `topics` : Identifies the topic name or a comma-separated list of topic names.
* Type: list * Importance: high `errors.deadletterqueue.topic.name` : The name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, or its transformations or converters. Defaults to ‘dlq-${connector}’ if not set. The DLQ topic will be created automatically if it does not exist. You can provide `${connector}` in the value to use it as a placeholder for the logical cluster ID.
* Type: string * Default: dlq-${connector} * 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 `secret.manager.enabled` : Fetch sensitive configuration values from a secret manager.
* Type: boolean * Default: false * 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 ### 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 ### Database details `collection` : MongoDB collection name.
* Type: string * Importance: medium ### ID strategies `doc.id.strategy` : The IdStrategy class name to use for generating a unique document id (_id).
* Type: string * Default: BsonOidStrategy * Importance: low `doc.id.strategy.overwrite.existing` : Whether the connector should overwrite existing values in the \_id field when the strategy defined in doc.id.strategy is applied.
* Type: boolean * Default: false * Importance: low `document.id.strategy.uuid.format` : The bson output format when using the UuidStrategy. Can be either String or Binary.
* Type: string * Default: string * Importance: low `key.projection.type` : For use with the PartialKeyStrategy allows custom key fields to be projected for the ID strategy. Use either AllowList or BlockList.
* Type: string * Default: none * Importance: low `key.projection.list` : For use with the PartialKeyStrategy allows custom key fields to be projected for the ID strategy. A comma-separated list of field names for key projection.
* Type: string * Importance: low `value.projection.type` : For use with the PartialValueStrategy allows custom value fields to be projected for the ID strategy. Use either AllowList or BlockList.
* Type: string * Default: none * Importance: low `value.projection.list` : For use with the PartialValueStrategy allows custom value fields to be projected for the ID strategy. A comma-separated list of field names for value projection.
* Type: string * Importance: low ### Namespace mapping `namespace.mapper.class` : The class that determines the namespace to write the sink data to. By default this will be based on the ‘database’ configuration and either the topic name or the ‘collection’ configuration.
* Type: string * Default: DefaultNamespaceMapper * Importance: low `namespace.mapper.key.database.field` : The key field to use as the destination database name.
* Type: string * Importance: low `namespace.mapper.key.collection.field` : The key field to use as the destination collection name.
* Type: string * Importance: low `namespace.mapper.value.database.field` : The value field to use as the destination database name.
* Type: string * Importance: low `namespace.mapper.value.collection.field` : The value field to use as the destination collection name.
* Type: string * Importance: low `namespace.mapper.error.if.invalid` : Whether to throw an error if the mapped field is missing or invalid. Defaults to false.
* Type: boolean * Default: false * Importance: low ### 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 ### Connection details `max.num.retries` : How many retries should be attempted on write errors.
* Type: int * Default: 3 * Valid Values: [0,…] * Importance: low `retries.defer.timeout` : How long a retry should get deferred.
* Type: int * Default: 5000 * Valid Values: [0,…] * Importance: low ### Time Series configuration `timeseries.timefield` : The name of the top-level field which contains the date in each time series document. Setting this config will create a time series collection where each document will have a BSON date as the value for the timefield.
* Type: string * Default: “” * Importance: low `timeseries.timefield.auto.convert` : Whether to convert the data in the field into a BSON Date format. Supported formats include integer, long, and string.
* Type: boolean * Default: false * Importance: low `timeseries.timefield.auto.convert.date.format` : The string pattern to convert the source data from. The setting expects the string representation to contain both date and time information and uses the Java DateTimeFormatter.ofPattern(pattern, locale) API for the conversion. If the string only contains date information, then the time since epoch is from the start of that day. If a string representation does not contain time-zone offset, then the setting interprets the extracted date and time as UTC.
* Type: string * Default: yyyy-MM-dd[[‘T’][ ]][HH:mm:ss[[.][SSSSSS][SSS]][ ]VV[ ]’[‘VV’]’][HH:mm:ss[[.][SSSSSS][SSS]][ ]X][HH:mm:ss[[.][SSSSSS][SSS]]] * Importance: low `timeseries.timefield.auto.convert.locale.language.tag` : The DateTimeFormatter locale language tag to use with the date pattern.
* Type: string * Default: en * Importance: low `timeseries.metafield` : The name of the top-level field that contains metadata in each time series document. This field groups related data. It can be of any type except array.
* Type: string * Default: “” * Importance: low `timeseries.expire.after.seconds` : The amount of seconds the data remains in MongoDB before MongoDB deletes it. Omitting this field means data will not be deleted automatically.
* Type: int * Default: 0 * Valid Values: [0,…] * Importance: low `ts.granularity` : The expected interval between subsequent measurements for a time-series. Set this to None or leave it empty if the data is not time-series
* Type: string * Default: None * Importance: low ### Error handling `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 ### Consumer configuration `max.poll.interval.ms` : The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).
* Type: long * Default: 300000 (5 minutes) * Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters * Importance: low `max.poll.records` : The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.
* Type: long * Default: 500 * Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters * Importance: low ### Number of tasks for this connector `tasks.max` : Maximum number of tasks for the connector.
* Type: int * Valid Values: [1,…] * Importance: high ### Post Processing `post.processor.chain` : A comma separated list of post processor classes to process the data before saving to MongoDB.
* Type: list * Default: com.mongodb.kafka.connect.sink.processor.DocumentIdAdder * Importance: low `field.renamer.mapping` : An inline JSON array with objects describing field name mappings. Example: `[{"oldName":"key.fieldA","newName":"field1"},{"oldName":"value.xyz","newName":"abc"}]`
* Type: string * Default: [] * Importance: low ### Additional Configs `consumer.override.auto.offset.reset` : Defines the behavior of the consumer when there is no committed position (which occurs when the group is first initialized) or when an offset is out of range. You can choose either to reset the position to the “earliest” offset (the default) or the “latest” offset. You can also select “none” if you would rather set the initial offset yourself and you are willing to handle out of range errors manually. More details: [https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset](https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset)
* Type: string * Importance: low `consumer.override.isolation.level` : Controls how to read messages written transactionally. If set to read_committed, consumer.poll() will only return transactional messages which have been committed. If set to read_uncommitted (the default), consumer.poll() will return all messages, even transactional messages which have been aborted. Non-transactional messages will be returned unconditionally in either mode. More details: [https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level](https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level)
* Type: string * Importance: low `header.converter` : The converter class for the headers. This is used to serialize and deserialize the headers of the messages.
* Type: string * Importance: low `key.converter.use.schema.guid` : The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema GUID to be used for deserializing message keys. Only applicable when key.converter.key.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: string * Importance: low `key.converter.use.schema.id` : The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema ID to be used for deserializing message keys. Only applicable when key.converter.key.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: int * 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.use.schema.guid` : The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema GUID to be used for deserializing message values. Only applicable when value.converter.value.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: string * Importance: low `value.converter.use.schema.id` : The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema ID to be used for deserializing message values. Only applicable when value.converter.value.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: int * 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: all * Importance: low `key.converter.key.schema.id.deserializer` : The class name of the schema ID deserializer for keys. This is used to deserialize schema IDs from the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.DualSchemaIdDeserializer * 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.schema.id.deserializer` : The class name of the schema ID deserializer for values. This is used to deserialize schema IDs from the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.DualSchemaIdDeserializer * 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 ## Suggested Reading Blog post: [Announcing the MongoDB Atlas Sink and Source connectors in Confluent Cloud](https://www.confluent.io/blog/confluent-cloud-offers-kafka-mongodb-connector-managed-clusters/) ## Frequently asked questions Find answers to frequently asked questions about the MongoDB Atlas Sink connector for Confluent Cloud. ### Why is my connector stuck in `PROVISIONING` state? If your connector remains in `PROVISIONING` state indefinitely without transitioning to `RUNNING`, this indicates the connector failed to complete the deployment process. Common causes and solutions: * **Invalid MongoDB credentials**: Verify your MongoDB connection host, username, and password are correctly configured. Test your credentials using a MongoDB client before configuring the connector. * **Connection host format**: Use the correct connection host format. For `MONGODB_ATLAS`, use a service record such as `cluster4-r5q3r7.gcp.mongodb.net`. For `MONGODB_SELF_MANAGED`, use a standard connection string such as `54.190.171.123:27017`. * **Network connectivity**: Ensure the connector can reach your MongoDB instance. If your MongoDB instance is not publicly accessible, verify that you have added all Confluent Cloud egress IP addresses to your MongoDB IP whitelist. For more information, see [Adding an IP Whitelist Entry](#cc-mongo-ip-whitelist-entry). * **Insufficient privileges**: Verify the database user has been granted either the `readWrite` role, or both the `readAnyDatabase` and `clusterMonitor` roles. For more information, see [Prerequisites](https://www.mongodb.com/docs/kafka-connector/current/introduction/connect/#prerequisites). * **Invalid collection name**: Verify the collection specified in the configuration exists or can be created by the connector. If the connector remains stuck after verifying these settings, delete and recreate the connector with the corrected configuration. ### Why does my connector fail with authentication errors? Authentication errors occur when the connector cannot authenticate with your MongoDB instance. Common causes and solutions: * **Incorrect credentials**: Verify your MongoDB username and password are correct. Test authentication using a MongoDB client to confirm credentials work. * **X.509 certificate issues**: If you use X.509 certificate authentication, ensure your certificate and private key are correctly formatted. The certificate should include the full chain and the private key should be in PEM format without a passphrase. * **Authentication source**: For `MONGODB_SELF_MANAGED` deployments, you may need to specify the `authSource` parameter in the connection host. For example: `54.190.171.123:27017/?authSource=admin`. * **Connection string format**: Do not include the username and password in the connection host string. Instead, provide them in the separate `connection.user` and `connection.password` fields. * **Insufficient database permissions**: Verify the user has `readWrite` permissions on the target database. For X.509 authentication setup, see [connector authentication](#cc-mongo-db-sink-setup-connection). ### How do I configure the connector to delete MongoDB documents when Kafka records have null values? To delete MongoDB documents when receiving Kafka records with null values, you must configure both `delete.on.null.values` and the appropriate document ID strategy. Required configuration: ```none "delete.on.null.values": "true", "doc.id.strategy": "FullKeyStrategy" ``` Supported document ID strategies for deletes: * **FullKeyStrategy**: Uses the entire Kafka record key as the MongoDB document `_id`. * **PartialKeyStrategy**: Uses a subset of key fields as the `_id`. Requires `key.projection.type` and `key.projection.list` settings. * **ProvidedInKeyStrategy**: Expects the `_id` to be provided in the key. Important considerations: * **Tombstone records**: When `delete.on.null.values` is `true`, the connector treats tombstone records with null values as delete operations. * **Key requirement**: The Kafka record must have a non-null key for deletes to work. Records without keys cannot be deleted. * **Write strategy**: The `write.strategy` must be compatible with deletes. `DeleteOneDefaultStrategy` is designed for delete operations. For more information, see the `doc.id.strategy` property in [Configuration Properties](#cc-mongodb-sink-config-properties). ### Which write strategy should I use? The `write.strategy` determines how the connector performs bulk write operations on MongoDB collections. Common write strategies: * **DefaultWriteModelStrategy**: Internally uses `ReplaceOneDefaultStrategy` for normal collections and `InsertOneDefaultStrategy` for time-series collections. Use this for most scenarios. * **ReplaceOneDefaultStrategy**: Replaces entire documents matching the `_id`. Best for upsert operations where you want to replace the full document. * **InsertOneDefaultStrategy**: Only inserts new documents. Fails if a document with the same `_id` already exists. Use for append-only workloads. * **UpdateOneDefaultStrategy**: Updates existing documents. Use when you want to modify specific fields without replacing the entire document. * **UpdateOneBusinessKeyTimestampStrategy**: Updates documents using a business key and timestamp. Useful for maintaining the latest version of a document based on timestamps. * **DeleteOneDefaultStrategy**: Deletes documents. Use with `delete.on.null.values=true` for CDC scenarios. To configure the write strategy: ```none "write.strategy": "ReplaceOneDefaultStrategy" ``` For detailed information about each write strategy, see [Write Strategies](https://www.mongodb.com/docs/kafka-connector/master/sink-connector/configuration-properties/write-strategies/). ### How do I handle connection string options for MongoDB? Specify connection string options in the `connection.host` property. For `MONGODB_ATLAS`, use the format: ```none cluster4-r5q3r7.gcp.mongodb.net/?readPreference=secondary&retryWrites=true ``` For `MONGODB_SELF_MANAGED`, use the format: ```none 54.190.171.123:27017/?authSource=admin&writeConcern=majority ``` Important considerations: * **Do not include protocol**: Do not include `mongodb://` or `mongodb+srv://` in the connection host. * **Do not include credentials**: Do not include username and password in the connection string. Use the separate `connection.user` and `connection.password` fields. * **Supported options**: Not all MongoDB connection string options are supported. For the list of unsupported options, see the connector documentation. * **Write concern**: For production workloads, consider setting `writeConcern=majority` to ensure writes are acknowledged by a majority of replica set members. For more information about connection string options, see [MongoDB Connection String Options](https://www.mongodb.com/docs/manual/reference/connection-string-options/). ### What should I set for the `max.batch.size` and `max.num.retries` properties? These properties control the connector’s write behavior and error handling. * **max.batch.size**: The maximum number of sink records to batch together for processing. Default is `0`, which means no limit. A value of `0` allows the connector to batch all available records, which provides maximum throughput but may increase latency. Lower this value if you experience connector memory issues or need lower latency. * **max.num.retries**: The number of times the connector retries on write errors. Default is `3`. Increase this value for production workloads to handle transient network issues. * **retries.defer.timeout**: The time in milliseconds to wait between retries. Default is `5000` ms. Adjust these values based on your specific workload requirements and monitor your connector’s error logs. ### How do I configure time-series collections? MongoDB time-series collections require specific configuration to properly store time-series data. Required configuration: * **timeseries.timefield**: Sets the name of the top-level time field that contains the date in each time-series document. This field must contain a BSON date. * **timeseries.timefield.auto.convert**: Set to `true` to automatically convert the time field data to BSON date format. Supported source formats include integer, long, and string. Default is `false`. Optional configuration: * **timeseries.timefield.auto.convert.date.format**: Sets the DateTimeFormatter format to convert the source data from. Default is `yyyy-MM-dd[['T'][ ]][HH:mm:ss[[.][SSSSSS][SSS]][ ]VV[ ]'['VV']'][HH:mm:ss[[.][SSSSSS][SSS]][ ]X][HH:mm:ss[[.][SSSSSS][SSS]]]`. * **timeseries.metafield**: Sets the name of the top-level field that contains metadata in each time-series document. * **timeseries.expire.after.seconds**: Sets the number of seconds after which the document expires. MongoDB deletes expired documents automatically. Default is `0`, which means data will not be deleted automatically. * **ts.granularity**: Sets the interval granularity. Valid entries are `None`, `seconds`, `minutes`, or `hours`. Default is `None`. Important considerations: * Time-series collections require MongoDB version 5.0 or later and are only available on dedicated clusters in MongoDB Atlas. * For time-series collections, `DefaultWriteModelStrategy` internally defaults to `InsertOneDefaultStrategy`. For more information, see the time-series properties in [Configuration Properties](#cc-mongodb-sink-config-properties). ## 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. [![image](images/topology.png)](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)