# Google Cloud Firestore Sink Connector for Confluent Cloud The fully managed Google Cloud Firestore Sink connector for Confluent Cloud streams data from Apache Kafka® topics into Google Cloud Firestore collections using the Firestore endpoint. The connector writes to Firestore through its Firestore [MongoDB-compatible API](https://cloud.google.com/products/firestore/mongodb-compatibility). Consequently, you address Firestore data by using MongoDB driver concepts: databases, collections, documents, binary JSON (BSON), and the `_id` field. This applies even though the underlying datastore is Firestore. Property names and ID strategies in this document reflect the MongoDB model. ## Features The Google Cloud Firestore Sink connector provides the following features: * **Database authentication**: Authenticates to the Firestore MongoDB-compatible endpoint by using a SCRAM username and password provisioned in the Google Cloud console. The connector does not use service account JSON authentication. * **Input data formats**: Supports Avro, JSON Schema (JSON_SR), Protobuf, or JSON (schemaless) 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). * **Configurable write strategies**: Controls the behavior of bulk write operations, including upserts, inserts, replacements, and deletes. * **Flexible document ID strategies**: Supports multiple strategies for generating unique document IDs, including BSON OID, full key, Kafka metadata, and custom field projections. * **Delete on null**: When enabled, the connector deletes a Firestore document when the corresponding Kafka record value is null. * **Client-side encryption (CSFLE and CSPE) support**: Supports CSFLE and CSPE for sensitive data. For more information about CSFLE or CSPE setup, see [Manage Client-Side Encryption for Fully Managed Connectors in Confluent Cloud](csfle.md#connect-csfle). * **Offset management capabilities**: Supports offset management. For more information, see [Manage offsets for Sink Connectors](offsets.md#custom-offsets-sink-proc). 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 [Google Cloud Firestore Sink Connector](limits.md#google-cloud-firestore-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). - If you plan to use one or more Custom SMTs, see [Custom SMT limitations](configure-custom-single-message-transforms/custom-smt-limitations-support.md#cc-custom-smt-limitations). ## Quick start Use this quick start to get up and running with the Confluent Cloud Google Cloud Firestore Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events from Kafka topics into Firestore collections. 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). - A Google Cloud project with Firestore enabled and the MongoDB-compatible API activated. For details, see [Use Firestore with MongoDB drivers](https://docs.cloud.google.com/firestore/mongodb-compatibility/docs/overview). - A Firestore database with the hostname and port. - A Firestore user with read and write permissions on the target database.
- Kafka cluster credentials. The following lists the different ways you can provide credentials. - Enter an existing [service account](service-account.md#s3-cloud-service-account) resource ID. - Create a Confluent Cloud [service account](service-account.md#s3-cloud-service-account) for the connector. Make sure to review the ACL entries required in the [service account documentation](service-account.md#s3-cloud-service-account). Some connectors have specific ACL requirements. - Create a Confluent Cloud API key and secret. To create a key and secret, you can use [confluent api-key create](https://docs.confluent.io/confluent-cli/current/command-reference/api-key/confluent_api-key_create.html) *or* you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector. ### Using the Confluent Cloud Console #### Step 1: Launch your Confluent Cloud cluster To create and launch a Kafka cluster in Confluent Cloud, see [Create a kafka cluster in Confluent Cloud](../get-started/index.md#cloud-create-kafka-cluster). #### Step 2: Add a connector In the left navigation menu, click **Connectors**. If you already have connectors in your cluster, click **+ Add connector**. #### Step 3: Select your connector Click the **Google Cloud Firestore Sink** connector card.  #### Step 4: Enter the connector details Before configuring the connector settings, ensure that you complete all [prerequisites](#cc-gcp-firestore-sink-prereqs). #### NOTE * An asterisk ( \* ) designates a required entry. At the **Google Cloud Firestore 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: **Firestore connection** - **Connection host**: The host name and port of the Google Cloud Firestore MongoDB-compatible endpoint. Expected format: `hostname:port`. **Authentication** - **Connection user**: The Google Cloud Firestore connection user. - **Connection password**: The Google Cloud Firestore connection password. **Firestore Database Details** - **Database name**: The Google Cloud Firestore database name. - **Collection name**: The Google Cloud Firestore collection name. If the connector sinks data from multiple topics, this is the default collection the topics are mapped to. **TLS Configuration** - **TLS**: Whether TLS is enabled on the connection. Default is `true`. 2. Click **Continue**. ### Configuration #### NOTE Configuration properties that are not shown in the Cloud Console use the default values. For all property values and definitions, see [Configuration properties](#cc-gcp-firestore-sink-config-properties). - **Kafka record value format**: Sets the input Kafka record value format. Valid entries are `AVRO`, `JSON_SR`, `PROTOBUF`, or `JSON`. You must have Confluent Cloud Schema Registry configured to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). **Data encryption** - Enable **Client-Side Field Level Encryption** for data encryption. Specify a **Service Account** to access the Schema Registry and associated encryption rules or keys with that schema. For more information on CSFLE or CSPE setup, see [Manage encryption for connectors](csfle.md#connect-csfle). ### **Show advanced configurations** - **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). - **Kafka record key format**: Sets the input Kafka record key format. Valid entries are `AVRO`, `BYTES`, `JSON`, `JSON_SR`, `PROTOBUF`, or `STRING`. - **Topic override map**: A JSON map to override sink connector properties for specific topics. Use 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 overridable properties include `collection`, `database`, `namespace.mapper.*`, `delete.on.null.values`, `writemodel.strategy`, `delete.writemodel.strategy`, `document.id.strategy.*`, `key.projection.*`, `value.projection.*`, `field.renamer.*`, `post.processor.chain`, `errors.tolerance`, `errors.log.enable`, `errors.deadletterqueue.topic.name`, `max.batch.size`, and `rate.limiting.timeout`. Properties that cannot be overridden include `connection.host`, `connection.user`, `connection.password`, `topics`, and `topic.override.*`. **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. **Write strategies** - **Write model strategy**: The class that specifies the WriteModel to use for bulk writes. - **Maximum batch size**: The maximum number of sink records to batch together for processing. `0` means no limit. - **Ordered bulk writes**: Whether bulk writes should be ordered. - **Rate limit timeout (ms)**: How long (in ms) to wait before sending the next batch when rate limiting is enabled. `0` means no rate limiting. - **Rate limit every N batches**: How many batches of records to send before applying rate limiting. `0` means no rate limiting. - **Delete on null values**: Whether the connector should delete documents when the value is null. - **Delete write model strategy**: The class that handles how to build the delete write models for the sink documents. **ID strategies** - **Document ID strategy**: The strategy to use for generating a unique document ID. - **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 key projection type**: For use with `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 `PartialKeyStrategy`, allows custom key fields to be projected for the ID strategy. Provide a comma-separated list of field names for key projection. - **Document ID strategy value projection type**: For use with `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 `PartialValueStrategy`, allows custom value fields to be projected for the ID strategy. Provide a comma-separated list of field names for value projection. **Namespace mapping** - **Namespace mapper**: The class that determines the database and collection to write to. - **Key database field**: The field in the key to use for the database name when using `FieldPathNamespaceMapper`. - **Key collection field**: The field in the key to use for the collection name when using `FieldPathNamespaceMapper`. - **Value database field**: The field in the value to use for the database name when using `FieldPathNamespaceMapper`. - **Value collection field**: The field in the value to use for the collection name when using `FieldPathNamespaceMapper`. - **Error if invalid namespace**: Whether to throw an error if the namespace mapping is invalid. **Error handling** - **Error tolerance**: Error tolerance level. Use `none` to fail on errors, or `all` to skip errors. **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). For all property values and definitions, see [Configuration properties](#cc-gcp-firestore-sink-config-properties). - Click **Continue**. ### Sizing Based on the number of topic partitions you select, you are provided with a recommended number of tasks. 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 1. Verify the connection details. 2. Click **Launch**. The status for the connector should go from **Provisioning** to **Running**. #### Step 5: Check the results in Firestore Check your Firestore database to verify that the connector has written documents to the target collection. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section. ### Using the Confluent CLI Complete the following steps to set up and run the connector using the Confluent CLI. #### NOTE Make sure you have all your [prerequisites](#cc-gcp-firestore-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 { "name": "FirestoreSinkConnector_0", "config": { "topics": "", "connector.class": "FirestoreSink", "name": "FirestoreSinkConnector_0", "input.data.format": "AVRO", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "", "kafka.api.secret": "", "connection.host": ":", "connection.user": "", "connection.password": "", "database": "", "tasks.max": "1" } } ``` Note the following property definitions: * `"name"`: Sets a name for your new connector. * `"connector.class"`: Identifies the connector plugin name. * `"topics"`: Identifies the topic name or a comma-separated list of topic names. * `"input.data.format"`: Sets the input Kafka record value format. Valid entries are `AVRO`, `JSON_SR`, `PROTOBUF`, or `JSON`. You must have Confluent Cloud Schema Registry configured to use a schema-based message format. * `"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 ``` * `"connection.host"`: The host name and port of the Google Cloud Firestore MongoDB-compatible endpoint. Use the format `hostname:port`. * `"connection.user"`: The Google Cloud Firestore connection user. * `"connection.password"`: The Google Cloud Firestore connection password. * `"database"`: The Google Cloud Firestore database name. * `"tasks.max"`: The maximum number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use. #### 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). For all properties and definitions, see [Configuration properties](#cc-gcp-firestore-sink-config-properties). #### Step 4: Load the configuration 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 gcp-firestore-sink-config.json ``` Example output: ```none Created connector FirestoreSinkConnector_0 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 | FirestoreSinkConnector_0 | RUNNING | sink ``` #### Step 6: Check the results in Firestore Check your Firestore database to verify that the connector has written documents to the target collection. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section. ## Configuration properties Use the following configuration properties with the fully managed connector. For self-managed connector property definitions and other details, see the connector docs in [/platform/current/Self-managed connectors for](/platform/current/Self-managed connectors for ) . ### 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. You must have Confluent Cloud Schema Registry configured to use a schema-based message format (for example, 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.
* Type: string * Default: STRING * Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING * Importance: high ### Write strategies `write.strategy` : The class that specifies the write model to use for bulk writes.
* Type: string * Default: DefaultWriteModelStrategy * Valid Values: DefaultWriteModelStrategy, DeleteOneDefaultStrategy, InsertOneDefaultStrategy, ReplaceOneBusinessKeyStrategy, ReplaceOneDefaultStrategy, UpdateOneBusinessKeyTimestampStrategy, UpdateOneDefaultStrategy, UpdateOneTimestampsStrategy * Importance: low `max.batch.size` : The maximum number of sink records to batch together for processing. `0` means no limit.
* Type: int * Default: 0 * Importance: medium `bulk.write.ordered` : Whether bulk writes are ordered.
* Type: boolean * Default: true * Importance: medium `rate.limiting.timeout` : How long to wait, in milliseconds, before sending the next batch if rate limit is enabled. `0` means no rate limit.
* Type: int * Default: 0 * Importance: low `rate.limiting.every.n` : How many batches of records to send before applying rate limit. `0` means no rate limit.
* Type: int * Default: 0 * Importance: low `delete.on.null.values` : Whether the connector deletes documents when the value is null.
* Type: boolean * Default: false * Importance: medium `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. Use 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 overridable properties include `collection`, `database`, `namespace.mapper.*`, `delete.on.null.values`, `writemodel.strategy`, `delete.writemodel.strategy`, `document.id.strategy.*`, `key.projection.*`, `value.projection.*`, `field.renamer.*`, `post.processor.chain`, `errors.tolerance`, `errors.log.enable`, `errors.deadletterqueue.topic.name`, `max.batch.size`, and `rate.limiting.timeout`.
Properties that cannot be overridden include `connection.host`, `connection.user`, `connection.password`, `topics`, and `topic.override.*`.
* Type: string * Default: {} * Importance: low ### ID strategies `doc.id.strategy` : The strategy to use for generating a unique document ID.
* Type: string * Default: BsonOidStrategy * Valid Values: BsonOidStrategy, FullKeyStrategy, KafkaMetaDataStrategy, PartialKeyStrategy, PartialValueStrategy, ProvidedInKeyStrategy, ProvidedInValueStrategy, UuidStrategy * Importance: high `doc.id.strategy.overwrite.existing` : Whether the connector overwrites existing values in the `_id` field when the strategy defined in `doc.id.strategy` is applied.
* Type: boolean * Default: false * Importance: low `key.projection.type` : When using the `PartialKeyStrategy`, this allows custom key fields to be projected for the ID strategy. Use either `allowlist` or `blocklist`.
* Type: string * Default: none * Valid Values: allowlist, blocklist, none * Importance: low `key.projection.list` : When using the `PartialKeyStrategy`, this allows custom key fields to be projected for the ID strategy. Provide a comma-separated list of field names for key projection.
* Type: string * Importance: low `value.projection.type` : When using the `PartialValueStrategy`, this allows custom value fields to be projected for the ID strategy. Use either `allowlist` or `blocklist`.
* Type: string * Default: none * Valid Values: allowlist, blocklist, none * Importance: low `value.projection.list` : When using the `PartialValueStrategy`, this allows custom value fields to be projected for the ID strategy. Provide a comma-separated list of field names for value projection.
* Type: string * 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 ### Firestore connection `connection.host` : The host name and port of the Firestore MongoDB-compatible endpoint. The expected format is `hostname:port`.
* Type: string * Default: “” * Importance: high `connection.user` : The name of the connection user connecting to the Firestore database.
* Type: string * Importance: high `connection.password` : The password for the connection user connecting to the Firestore database.
* Type: password * Importance: high `database` : The name of the Firestore database to connect to.
* Type: string * Importance: high `collection` : The name of the Firestore collection name used to store events from Kafka topics.
* Type: string * Importance: medium `connection.tls.enabled` : Specify whether to use Transport Layer Security (TLS) to connect to the Firestore database.
* Type: boolean * Default: true * Importance: high ### Namespace mapping `namespace.mapper.class` : The class that determines the database and collection to write to.
* Type: string * Default: DefaultNamespaceMapper * Valid Values: DefaultNamespaceMapper, FieldPathNamespaceMapper * Importance: low `namespace.mapper.key.database.field` : The field in the key to use for the database name when using `FieldPathNamespaceMapper`.
* Type: string * Default: “” * Importance: low `namespace.mapper.key.collection.field` : The field in the key to use for the collection name when using `FieldPathNamespaceMapper`.
* Type: string * Default: “” * Importance: low `namespace.mapper.value.database.field` : The field in the value to use for the database name when using `FieldPathNamespaceMapper`.
* Type: string * Default: “” * Importance: low `namespace.mapper.value.collection.field` : The field in the value to use for the collection name when using `FieldPathNamespaceMapper`.
* Type: string * Default: “” * Importance: low `namespace.mapper.error.if.invalid` : Whether to throw an error if the namespace mapping is invalid.
* Type: boolean * Default: false * Importance: low ### Error handling `firestore.errors.tolerance` : The error tolerance level. Use `none` to fail on errors, or `all` to skip errors.
* Type: string * Default: none * 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 Google Cloud Firestore Sink connector for Confluent Cloud. ### Why does the connector use MongoDB concepts like collections and `_id` instead of Firestore native concepts? The connector writes to Firestore through its MongoDB-compatible API. The MongoDB-compatible API exposes Firestore data using MongoDB driver constructs: databases, collections, documents, BSON, and the `_id` field. The connector uses these constructs throughout its configuration and behavior, even though the underlying datastore is Firestore. This means: * `database` maps to a Firestore database. * `collection.name` maps to a Firestore collection. * Document IDs are controlled by `document.id.strategy`, not by a Firestore-native key field. The native Firestore API is not used. For more information, see [Google Cloud Firestore Sink Connector](limits.md#google-cloud-firestore-sink-limits). ### Why can’t I authenticate with a Google service account JSON key? The connector authenticates to the Firestore MongoDB-compatible endpoint using SCRAM credentials (a username and password), not a service account JSON key. This is a requirement of the MongoDB-compatible API, which does not accept IAM-based service account authentication. To obtain SCRAM credentials, provision a Firestore database user in the Google Cloud console under **Firestore > MongoDB-compatible API**. Supply the resulting username and password in `connection.user` and `connection.password`. ### My connector is creating duplicate documents. How do I fix this? The default write mode inserts new documents and does not update existing ones. If the connector restarts, reprocesses records, or the same key is produced more than once, duplicate documents or insert errors can result. **Solution:** Set `writemodel.strategy` to `ReplaceOneDefaultStrategy` or `UpdateOneTimestampsStrategy` to perform upserts based on the document `_id`: ```json { "writemodel.strategy": "ReplaceOneDefaultStrategy" } ``` `ReplaceOneDefaultStrategy` replaces the full document on match. `UpdateOneTimestampsStrategy` updates existing documents and adds `_insertedAt` or `_modifiedAt` timestamps. For more information, see `writemodel.strategy` in [Configuration properties](#cc-gcp-firestore-sink-config-properties). ### How do I delete a Firestore document from a Kafka tombstone record? Enable `delete.on.null.values`: ```json { "delete.on.null.values": "true" } ``` When this is set, the connector deletes the Firestore document whose `_id` matches the Kafka record key whenever it receives a record with a `null` value (a tombstone). The write strategy must support deletes. Use either `DeleteOneDefaultStrategy` or a strategy that issues delete operations. ### How do I control which field becomes the Firestore document `_id`? Use `document.id.strategy` to choose how the connector generates each document’s `_id`: * `BsonOidStrategy`: Generates a new BSON ObjectId for every record. Documents are always inserted and duplicates are not detected. * `FullKeyStrategy`: Uses the entire Kafka record key as the `_id`. Good for natural keys. * `KafkaMetaDataStrategy`: Combines the topic, partition, and offset into the `_id`. * `PartialKeyStrategy` / `PartialValueStrategy`: Uses a subset of key or value fields specified by `document.id.strategy.partial.key.projection.list` or the value equivalent. For upsert and delete behavior to work correctly, use a deterministic strategy (`FullKeyStrategy` or a `Partial*` strategy) so that the same Kafka key always maps to the same Firestore document `_id`. ### Why does the connector require Schema Registry for Avro, JSON Schema, and Protobuf? Avro, JSON Schema (`JSON_SR`), and Protobuf formats embed a schema ID in each Kafka record rather than the full schema. The connector calls Confluent Cloud Schema Registry at runtime to resolve that ID to the full schema, which it uses to deserialize the record and map fields to BSON. Without Confluent Cloud Schema Registry enabled and configured, the connector cannot deserialize these formats. Use `JSON` (schemaless) if you do not have Confluent Cloud Schema Registry available. In that case, the connector maps the raw JSON object to a BSON document directly. ### The connector fails to connect to Firestore. What should I check? **Check the connection host format.** `connection.host` must be in `hostname:port` format, for example `..firestore.goog:443`. Including a URI scheme (`mongodb://`) or omitting the port causes a connection failure. **Check that the MongoDB-compatible API is activated.** In the Google Cloud console, navigate to **Firestore** and confirm the MongoDB-compatible API is enabled for your database. Connections to a Firestore database running in native mode are not supported. For more information, see [Google Cloud Firestore Sink Connector](limits.md#google-cloud-firestore-sink-limits). **Verify SCRAM credentials.** Confirm the username and password in `connection.user` and `connection.password` match a database user provisioned in the MongoDB-compatible API settings, not an IAM user or a service account. **Check private networking.** The connector does not support private networking. The Firestore endpoint must be publicly reachable from Confluent Cloud. For more information, see [Google Cloud Firestore Sink Connector](limits.md#google-cloud-firestore-sink-limits). ## 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)