# Amazon DocumentDB Sink Connector for Confluent Cloud The fully managed Amazon DocumentDB Sink connector for Confluent Cloud maps and persists events from Apache Kafka® topics directly to a DocumentDB database collection. The connector supports AVRO, JSON Schema, PROTOBUF, JSON (schemaless) or STRING data from Apache Kafka® topics. The connector ingests events from Kafka topics directly into a DocumentDB database, exposing the data to services for querying, enrichment, and analytics. #### NOTE * 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 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 AWS IAM role based authentication, through the provider integration framework. For more information DocumentDB authentication setup, see [connector authentication](#cc-document-db-sink-setup-connection). * **Input data formats:** The connector supports AVRO, JSON Schema, PROTOBUF, JSON (schemaless) or STRING 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). * **Offset management capabilities**: The connector supports offset management. For more information, see [Manage custom offsets](../offsets.md#custom-offsets-sink-proc). * **Multiple tasks**: The connector supports running one or more tasks. More tasks may improve performance. * **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-document-db-sink-setup-connection). * **Dead letter queue (DLQ) support**: The connector supports DLQ and routes invalid records to DLQ when configured. 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. #### NOTE The connector is compatible with Amazon DocumentDB engine versions 4.0, 5.0, and 8.0. It does not support connections to Amazon DocumentDB elastic clusters. ## Limitations Be sure to review the following information. * For connector limitations, see [Amazon DocumentDB Sink Connector](../limits.md#cc-amazon-documentdb-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 Amazon DocumentDB 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 DocumentDB 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 DocumentDB cluster located in the same region as your Kafka cluster. - For private networking setup, see [Private networking setup](#cc-document-db-sink-connect-to-cluster). - Generate a valid truststore file using the [AWS Truststore script](https://docs.aws.amazon.com/documentdb/latest/developerguide/connect_programmatically.html#connect_programmatically-tls_enabled). - 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. ### Private networking setup Review the following networking requirements and resources: * For general 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). * Private networking is only supported for Kafka clusters running on AWS. If your cluster is in another cloud provider, you must use a public endpoint for the DocumentDB cluster. * To enable cross-cloud connectivity, contact Confluent [Support](https://support.confluent.io/). When enabled, the connector must use the `tlsAllowInvalidHostnames` property to connect to the DocumentDB cluster. Amazon DocumentDB does not allow external network connections from the internet. To connect to DocumentDB, use one of the following private networking methods: 1. VPC peering (recommended): Follow the steps in [Use AWS VPC Peering with Confluent Cloud](../../networking/peering/aws-peering.md#cloud-networking-peering-aws) to set up a VPC peering connection. For DNS forwarding, use the domain docdb.amazonaws.com. 2. Egress PrivateLink endpoints: Follow the steps in [Egress PrivateLink Endpoints Setup Guide: DocumentDB on AWS for Confluent Cloud](../networking/aws-eap-documentdb.md#cc-aws-eap-documentdb) to configure a PrivateLink endpoint. The DocumentDB cluster and the Kafka cluster must reside in the same region. 3. Private Network Interface (PNI): Configure egress routes on your PNI access point to reach your DocumentDB cluster. For details, see [Use Private Network Interface on Confluent Cloud](../../networking/aws-pni.md#pni-overview-aws). ### 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 **Amazon DocumentDB Sink** connector card.  #### Step 4: Enter the connector details #### NOTE * Ensure you have all your [prerequisites](#cc-document-db-sink-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add Amazon DocumentDB 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: **DocumentDB connection** - **Connection host**: The host name and port of the AWS DocumentDB cluster. Expected format hostname:port. **Authentication method** - **Authentication method**: Choose an authentication mechanism for DocumentDB. Use SCRAM for username/password authentication, or IAM Roles. - **Provider Integration**: Select an existing integration that has access to your resource. In case you need to integrate a new IAM role, use provider integration - **Connection user**: DocumentDB connection user. - **Connection password**: DocumentDB connection password. **DocumentDB Database Details** - **Database name**: DocumentDB database name. - **Collection name**: DocumentDB collection name. **TLS Configuration** - **TLS**: Whether TLS is enabled on the cluster. - **SSL truststore file**: The trust store file containing trusted certificates in JKS format. This is required when TLS is enabled. - **SSL truststore password**: The password for the trust store file. 2. Click **Continue**. ### Configuration #### NOTE See [Configuration Properties](#cc-documentdb-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 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. **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 **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. **Writes** - **Write Model Strategy**: The class that specifies the WriteModel to use for bulk writes. - **Max batch size**: The maximum number of sink records to possibly batch together for processing. - **Use ordered bulk writes**: Whether the batches controlled by ‘max.batch.size’ must be written via ordered bulk writes. - **Rate limiting timeout**: How long in ms processing should wait before continuing after triggering a rate limit. - **Rate limiting batch number**: The number of processed batches that will trigger rate limiting. The default value of 0 sets no rate limiting. - **Delete on null values**: Whether or not the connector should try to delete documents based on key when value is null. **ID strategies** - **Document ID strategy**: The IdStrategy class name to use for generating a unique document id (_id). **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. - **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** - **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**. #### Step 5: Check Amazon DocumentDB After the connector is running, verify that messages are populating your Amazon DocumentDB 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-document-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": "AmazonDocumentDBSink", "name": "confluent-documentdb-sink", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "", "kafka.api.secret": "", "input.data.format" : "JSON", "connection.host": "", "connection.user": "", "connection.password": "", "topics": "", "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, or STRING. 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 DocumentDB host with connection string options. Use a hostname address and not a full URL. For example, use `example.cluster-example.us-west-2.docdb.amazonaws.com:27017`. The port number is optional and defaults to 27017. #### NOTE * The connector does not support following connection string options in `connection.host` configuration property: `tlsCertificateKeyFile`, `tlsCertificateKeyFilePassword`, `tlsCAFile`, `tlsAllowInvalidCertificates`, `tlsInsecure`, `tlsAllowInvalidHostnames`, `authMechanism`, `authMechanismProperties`, `gssapiServiceName`. * Other options like `readPreference`, `readConcernLevel`, or `w` defined in [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 property. For example, `example.cluster-example.us-west-2.docdb.amazonaws.com:27017/?readPreference=secondary&readConcernLevel=local&appName=test&w=majority`. * `"collection"`: The DocumentDB 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). * `"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). * `"write.strategy"`: Sets the write model for bulk write operations. Valid entries are `DefaultWriteModelStrategy`, `ReplaceOneDefaultStrategy`, `InsertOneDefaultStrategy` or `UpdateOneDefaultStrategy`. If not used, this property defaults to `DefaultWriteModelStrategy`. For detailed information about each write strategy, see [Strategies](https://www.mongodb.com/docs/kafka-connector/master/sink-connector/configuration-properties/write-strategies/#strategies). * Enter the number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector. For more information, see Confluent Cloud [connector limitations](../limits.md#cc-amazon-documentdb-sink-limits). #### 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 more information about adding SMTs using the Confluent CLI, see the [Single Message Transformations](../single-message-transforms.md#cc-single-message-transforms). For all property values and definitions, see [Configuration Properties](#cc-documentdb-sink-config-properties). #### 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 amazon-document-db-sink.json ``` Example output: ```none Created connector confluent-documentdb-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-documentdb-sink | RUNNING | sink ``` #### Step 6: Check DocumentDB After the connector is running, verify that records are populating your DocumentDB database. ## Configuration Properties Use the following configuration properties with the fully managed connector. ### 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 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 `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 ### Writes `max.batch.size` : The maximum number of sink records to possibly batch together for processing.
* Type: int * Default: 0 * Valid Values: [0,…] * 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 `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.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 * Valid Values: DefaultWriteModelStrategy, InsertOneDefaultStrategy, ReplaceOneDefaultStrategy, UpdateOneDefaultStrategy * Importance: low `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 ### ID strategies `doc.id.strategy` : The IdStrategy class name to use for generating a unique document id (_id).
* Type: string * Default: BsonOidStrategy * 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 Amazon DocumentDB database? `connection.host` : The host name and port of the AWS DocumentDB cluster. Expected format hostname:port.
* Type: string * Default: “” * Importance: high `authentication.method` : Choose an authentication mechanism for DocumentDB. Use SCRAM for username/password authentication, or IAM Roles.
* Type: string * Default: SCRAM * Valid Values: IAM Roles, SCRAM * Importance: high `connection.user` : DocumentDB connection user.
* Type: string * Importance: high `provider.integration.id` : Select an existing integration that has access to your resource. In case you need to integrate a new IAM role, use provider integration
* Type: string * Importance: high `connection.password` : DocumentDB connection password.
* Type: password * Importance: high `database` : DocumentDB database name.
* Type: string * Importance: high `collection` : DocumentDB collection name.
* Type: string * Importance: medium `connection.tls.enabled` : Whether TLS is enabled on the cluster.
* Type: boolean * Default: true * Importance: high `connection.ssl.truststore.file` : The trust store file containing trusted certificates in JKS format. This is required when TLS is enabled.
* Type: password * Default: [hidden] * Importance: medium `connection.ssl.truststorePassword` : The password for the trust store file.
* Type: password * Default: [hidden] * Importance: medium ### Namespace mapping `namespace.mapper.class` : The namespace mapper specifies which database or collection to sink the data to. The default `DefaultNamespaceMapper` uses values specified in the `database` and `collection` properties. If you configure your sink connector to use the `FieldPathNamespaceMapper`, you can specify which database and collection to sink a document based on the data’s field values.
* Type: string * Default: DefaultNamespaceMapper * Importance: low `namespace.mapper.key.database.field` : The key field to use as the destination database name, when using `FieldPathNamespaceMapper`
* Type: string * Importance: low `namespace.mapper.key.collection.field` : The key field to use as the destination collection name, when using `FieldPathNamespaceMapper`
* Type: string * Importance: low `namespace.mapper.value.database.field` : The value field to use as the destination database name, when using `FieldPathNamespaceMapper`
* Type: string * Importance: low `namespace.mapper.value.collection.field` : The value field to use as the destination collection name, when using `FieldPathNamespaceMapper`
* 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, in which case the connector falls back to the `database` and `collection` configuration properties. When set to true, the connector does not process documents missing the mapped field or that contain an invalid BSON type. The connector may halt or skip processing depending on the related error-handling configuration settings.
* Type: boolean * Default: false * Importance: low ### Error handling `documentdb.errors.tolerance` : Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework.
* Type: string * Default: ALL * Valid Values: ALL, 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 ### 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 ## Frequently asked questions Find answers to frequently asked questions about the Amazon DocumentDB Sink connector for Confluent Cloud. ### Why does my connector fail with `PKIX path building failed` or SSL handshake errors? This error occurs when the connector cannot validate the TLS certificate presented by your DocumentDB cluster: ```none com.mongodb.MongoTimeoutException: Timed out after 30000 ms while waiting to connect Caused by: javax.net.ssl.SSLHandshakeException: PKIX path building failed Caused by: sun.security.provider.certpath.SunCertPathBuilderException: unable to find valid certification path to requested target ``` Common causes and solutions: * **Missing truststore file**: The connector requires a truststore file containing the Amazon DocumentDB certificate authority when TLS is enabled. Generate the truststore file using the [AWS Truststore script](https://docs.aws.amazon.com/documentdb/latest/developerguide/connect_programmatically.html#connect_programmatically-tls_enabled) and upload it to the connector configuration. * **TLS not enabled in connector**: If your DocumentDB cluster has TLS enabled, you must also enable TLS in the connector configuration. Verify that `connection.tls.enabled` is set to `true`. * **Incorrect truststore password**: Ensure the truststore password matches the password used when generating the truststore file. * **Expired or invalid certificate**: Download the latest Amazon DocumentDB certificate bundle and regenerate your truststore file. To resolve this issue, upload the truststore file in the connector configuration and enable TLS: ```none "connection.tls.enabled": "true", "connection.ssl.truststore.file": "", "connection.ssl.truststorePassword": "" ``` ### Why does my connector fail with authentication errors? Authentication failures occur when the connector can’t validate your DocumentDB credentials. Review the following common causes and solutions: * **Incorrect username or password**: Verify that `connection.user` and `connection.password` contain valid DocumentDB credentials. Check for typos or special characters that may require escaping. * **User not created in DocumentDB**: Verify that the database user exists in your DocumentDB cluster and has been granted appropriate permissions on the target database and collection. * **Wrong authentication database**: DocumentDB uses the `admin` database for authentication by default. Verify that your user is created in the correct authentication database. * **IAM authentication issues**: If you’re using Amazon IAM role authentication, verify that the IAM role has the necessary DocumentDB permissions and the trust policy allows the Confluent Cloud service principal to assume the role. * **Insufficient database permissions**: The user must have `readWrite` permissions on the target database and collection. For auto-creation of collections, additional `dbAdmin` permissions may be required. For username and password authentication, verify your credentials: ```none "connection.user": "", "connection.password": "" ``` For Amazon IAM role authentication, configure the provider integration framework as described in [connector authentication](#cc-document-db-sink-setup-connection). ### Why does my connector fail with `Timed out after 30000 ms while waiting to connect`? This error indicates that the connector can’t establish a network connection to your DocumentDB cluster. ```text com.mongodb.MongoTimeoutException: Timed out after 30000 ms while waiting to connect ``` Review the following common causes and solutions: * **Network connectivity issues**: DocumentDB doesn’t allow external connections from the internet. Verify that you configured private networking using VPC peering or Amazon PrivateLink. For setup instructions, see [Private networking setup](#cc-document-db-sink-connect-to-cluster). * **Incorrect hostname or port**: Verify that the `connection.host` property uses the correct DocumentDB cluster endpoint. Use only the hostname without the `mongodb://` prefix. For example: `docdb-cluster.cluster-xxxxx.us-east-1.docdb.amazonaws.com:27017`. * **Security group rules**: Verify that your DocumentDB security group allows inbound traffic from your Confluent Cloud cluster’s VPC or egress PrivateLink endpoint. * **Region mismatch**: When you use Amazon PrivateLink, verify that your DocumentDB cluster and Kafka cluster are in the same Amazon region. * **DNS resolution issues**: If you’re using VPC peering, verify that DNS forwarding is configured for the `docdb.amazonaws.com` domain. For more information, see [Use AWS VPC Peering with Confluent Cloud](../../networking/peering/aws-peering.md#cloud-networking-peering-aws). To resolve connectivity issues, verify your private networking setup and security group rules. For VPC peering, verify that DNS forwarding is enabled for the DocumentDB domain. ### Why does my connector fail with `no subject alternative DNS name` errors? This error occurs when the TLS certificate’s hostname doesn’t match the connection hostname. ```text javax.net.ssl.SSLHandshakeException: No subject alternative DNS name matching found ``` Review the following common causes and solutions: * **Using instance endpoint instead of cluster endpoint**: Always use the DocumentDB cluster endpoint rather than individual instance endpoints. The TLS certificate is issued for the cluster endpoint. * **Cross-cloud connectivity**: If you’re connecting across cloud providers such as Azure or Google Cloud to Amazon DocumentDB, you may need to disable hostname validation. Set `tlsAllowInvalidHostnames` to `true` in the connection string options. Contact Confluent [Support](https://support.confluent.io/) to enable cross-cloud connectivity. * **PrivateLink DNS mismatch**: When you use Amazon PrivateLink, verify that the endpoint service name is correctly configured and DNS resolution points to the PrivateLink endpoint. To use the cluster endpoint, configure your connection host as follows: ```json { "connection.host": "docdb-cluster.cluster-xxxxx.us-east-1.docdb.amazonaws.com:27017" } ``` For cross-cloud connections after enabling with support, add the following to your connection string options: ```json { "connection.host": "docdb-cluster.cluster-xxxxx.us-east-1.docdb.amazonaws.com:27017/?tlsAllowInvalidHostnames=true" } ``` ### Why does my connector fail with `Connection string options are not supported`? This error occurs when you use unsupported connection string options in the `connection.host` property. The connector doesn’t support all MongoDB connection string options. The following options aren’t supported: * **TLS/SSL options**: `tlsCertificateKeyFile`, `tlsCertificateKeyFilePassword`, `tlsCAFile`, `tlsAllowInvalidCertificates`, `tlsInsecure` * **Authentication options**: `authMechanism`, `authMechanismProperties`, `gssapiServiceName` These options are managed through dedicated connector configuration properties rather than connection string options. To configure authentication and TLS, use the connector’s dedicated configuration properties: ```json { "connection.host": "docdb-cluster.cluster-xxxxx.us-east-1.docdb.amazonaws.com:27017", "connection.tls.enabled": "true", "connection.user": "", "connection.password": "" } ``` ### How do I configure private networking for DocumentDB? Amazon DocumentDB does not allow external network connections from the internet. You must use private networking to connect from Confluent Cloud. For detailed instructions on configuring private networking, including VPC peering and PrivateLink setup, see [Private networking setup](#cc-document-db-sink-connect-to-cluster). ### How can I improve connector performance and reduce lag? To optimize connector performance and throughput, review the following options: * **Increase the number of tasks**: Set a higher `tasks.max` value to process more partitions in parallel. One task can handle up to 100 partitions. More tasks improve throughput for multi-partition topics. * **Tune batch size**: Adjust `max.batch.size` to write larger batches to DocumentDB. Larger batches reduce the number of write operations and improve efficiency. The default is 0, which means no batching. Set this to a value greater than 0 to enable bulk write operations. * **Monitor consumer lag**: Configure `max.poll.records` and `max.poll.interval.ms` to balance Kafka consumption with DocumentDB write latency. * **Scale DocumentDB cluster**: If the connector is healthy but lag persists, the bottleneck may be DocumentDB cluster capacity. Monitor DocumentDB metrics in the Amazon console and consider scaling your cluster. Monitor connector metrics in the Cloud Console to identify bottlenecks and adjust your configuration. ## 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)