Salesforce Bulk API 2.0 Sink Connector for Confluent Cloud

The fully-managed Salesforce Bulk API 2.0 Sink connector for Confluent Cloud integrates Salesforce.com with Apache Kafka®. The connector performs insert, update, and delete operations on Salesforce SObjects using records available in Kafka topics and writes them to Salesforce. This connector uses Salesforce Bulk API 2.0.

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.
The connector supports Salesforce up to API version 65.0.

Features

The Salesforce Bulk API 2.0 Sink connector provides the following features:

API 2.0: Supports Salesforce Bulk API 2.0.
At least once delivery: The connector guarantees that records are delivered at least once to the Kafka topic. If the connector restarts, there could be duplicate records in the Kafka topic.
Supported data formats: The connector supports Avro, JSON Schema (JSON_SR), and Protobuf output data. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR, or Protobuf). See Schema Registry Enabled Environments for additional information.
Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance (that is, consumer lag is reduced with multiple tasks running).
Supports Salesforce relationship fields: The connector supports Salesforce relationship fields. For more information, see Salesforce relationship fields.
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.
Supports Multiple SObjects: Each connector instance supports up to five SObjects, provided that every selected topic is mapped to exactly one unique SObject. For each SObject, you must provide the object type and a comma-separated list of associated topics, ensuring that no single topic contains records for multiple SObjects.

Supports Client Credentials flow: The connector supports authentication using the Client Credentials flow that enables connecting to Salesforce without exposing the user credentials. To use CLIENT_CREDENTIALS grant type, you must enable the Client Credentials flow in your connected Salesforce application and assign an integration user.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Salesforce relationship fields

The connector supports Salesforce relationship fields that allow you to integrate external data fields within Salesforce sObjects, enhancing data aggregation and business processes. This is useful for populating Lookup relationships using values from external systems (External IDs).

Note

This connector does not currently support polymorphic fields.

Prerequisites

A Salesforce lookup field must already exist on your target sObject (for example, RelatedAccount__c pointing to the Account object).
The related object must have an indexed field or an External ID field (for example, External_Account_ID__c) to facilitate the relationship mapping.

Process relationship fields

Follow the steps below to process Salesforce relationship fields in your connector:

Enable relationship field

When you configure a sink connector, you must enable relationship field support. In your connector configuration, set the following parameters to false:

"skip.objectN.relationship.fields": "false"
"salesforce.objectN.ignore.reference.fields": "false"

Sample Configuration: Below is a sample configuration for a sink connector targeting a custom object (RelationshipDemo__c).

{
"config": {
"schema.context.name": "default",
"input.data.format": "AVRO",
"connector.class": "SalesforceBulkApiV2Sink",
"name": "SalesforceBulkApiV2SinkConnector_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "E2G767UJZGO5JSMR",
"kafka.api.secret": "",
"salesforce.grant.type": "CLIENT_CREDENTIALS",
"salesforce.instance": "https://login.salesforce.com/",
"salesforce.consumer.key": "",
"salesforce.consumer.secret": "*******************************************",
"salesforce.object.num": 1,
"salesforce.object1": "RelationshipDemo__c",
"salesforce.object1.topics": "RelationshipDemoTopic",
"salesforce.object1.use.custom.id.field": "false",
"salesforce.object1.ignore.reference.fields": "false",
"skip.object1.relationship.fields": "false",
"salesforce.object1.override.event.type": "false",
"salesforce.object1.sink.object.operation": "upsert",
"salesforce.version": "65.0",
"behavior.on.api.errors": "ignore",
"request.max.retries.time.ms": "30000",
"max.timeout.ms": "200000",
"max.poll.interval.ms": "300000",
"max.poll.records": "500",
"tasks.max": "1",
"value.converter.decimal.format": "BASE64",
"value.converter.reference.subject.name.strategy": "DefaultReferenceSubjectNameStrategy",
"errors.tolerance": "all",
"value.converter.value.subject.name.strategy": "TopicNameStrategy",
"key.converter.key.subject.name.strategy": "TopicNameStrategy",
"value.converter.ignore.default.for.nullables": "false",
"auto.restart.on.user.error": "true"
}
}

Associated Avro schema for sink topic

To use a relationship field, the Avro schema for the sink topic must define the relationship object (RelatedAccount__r) and the specific external field used for the lookup. In the schema below, RelatedAccount__r is used to resolve and populate the RelatedAccount__c field in Salesforce. The relationship field, RelatedAccount__r, is controlled by the external ID field, External_Account_ID__c.

Avro Schema: The following schema defines the structure for the RelationshipDemo__c sink topic.

{
  "connect.name": "io.confluent.salesforce.RelationshipDemo__c",
  "fields": [
    {
      "name": "Id",
      "type": {
        "connect.doc": "Unique identifier for the object.",
        "type": "string"
      }
    },
    {
      "default": null,
      "name": "OwnerId",
      "type": [
        "null",
        "string"
      ]
    },
    {
      "default": null,
      "name": "IsDeleted",
      "type": [
        "null",
        "boolean"
      ]
    },
    {
      "default": null,
      "name": "Name",
      "type": [
        "null",
        "string"
      ]
    },
    {
      "default": null,
      "name": "CreatedDate",
      "type": [
        "null",
        {
          "connect.name": "org.apache.kafka.connect.data.Timestamp",
          "connect.version": 1,
          "logicalType": "timestamp-millis",
          "type": "long"
        }
      ]
    },
    {
      "default": null,
      "name": "CreatedById",
      "type": [
        "null",
        "string"
      ]
    },
    {
      "default": null,
      "name": "LastModifiedDate",
      "type": [
        "null",
        {
          "connect.name": "org.apache.kafka.connect.data.Timestamp",
          "connect.version": 1,
          "logicalType": "timestamp-millis",
          "type": "long"
        }
      ]
    },
    {
      "default": null,
      "name": "LastModifiedById",
      "type": [
        "null",
        "string"
      ]
    },
    {
      "default": null,
      "name": "SystemModstamp",
      "type": [
        "null",
        {
          "connect.name": "org.apache.kafka.connect.data.Timestamp",
          "connect.version": 1,
          "logicalType": "timestamp-millis",
          "type": "long"
        }
      ]
    },
    {
      "default": null,
      "name": "LastViewedDate",
      "type": [
        "null",
        {
          "connect.name": "org.apache.kafka.connect.data.Timestamp",
          "connect.version": 1,
          "logicalType": "timestamp-millis",
          "type": "long"
        }
      ]
    },
    {
      "default": null,
      "name": "LastReferencedDate",
      "type": [
        "null",
        {
          "connect.name": "org.apache.kafka.connect.data.Timestamp",
          "connect.version": 1,
          "logicalType": "timestamp-millis",
          "type": "long"
        }
      ]
    },
    {
      "name": "RelatedAccount__r",
      "type": {
        "connect.name": "RelatedAccount__r",
        "fields": [
          {
            "default": null,
            "name": "External_Account_ID__c",
            "type": [
              "null",
              "string"
            ]
          }
        ],
        "name": "RelatedAccount__r",
        "type": "record"
      }
    },
    {
      "default": null,
      "name": "_ObjectType",
      "type": [
        "null",
        "string"
      ]
    },
    {
      "default": null,
      "name": "_EventType",
      "type": [
        "null",
        "string"
      ]
    }
  ],
  "name": "RelationshipDemo__c",
  "namespace": "io.confluent.salesforce",
  "type": "record"
}

Sample sink record

When sending records to the sink connector for RelationshipDemo__c, use the relationship field (RelatedAccount__r) to specify the external ID of the related record.

{
  "Id": "a00gL00000P85iUQAW",
  "OwnerId": {
    "string": "005gL000005tlt3QAA"
  },
  "IsDeleted": {
    "boolean": false
  },
  "Name": {
    "string": "DemoEntity"
  },
  "CreatedDate": {
    "long": 1761736099000
  },
  "CreatedById": {
    "string": "005gL000005tlt3QAA"
  },
  "LastModifiedDate": {
    "long": 1761736099000
  },
  "LastModifiedById": {
    "string": "005gL000005tlt3QAA"
  },
  "SystemModstamp": {
    "long": 1761736099000
  },
  "LastViewedDate": null,
  "LastReferencedDate": null,
  "RelatedAccount__r": {
    "External_Account_ID__c": {
      "string": "123456"
    }
  },
  "_ObjectType": {
    "string": "RelationshipDemo__c"
  },
  "_EventType": {
    "string": "created"
  }
}

Upon processing this record, a new RelationshipDemo sObject named DemoEntity is created. The connector automatically populates the RelatedAccount__c field with the accountId of the DemoAccount that matches the External_Account_ID__c value of 123456.

Common issues and resolutions

Issue	Potential Cause	Resolution
`Cannot specify both an external ID reference RelatedAccount__r and a salesforce id, RelatedAccount__c`	The record or schema includes both the lookup field (`__c`) and the relationship reference (`__r`). Salesforce requires only one identifier for sink operations.	Ensure the record schema uses only one field type. If source data is mixed, route different field types to separate topics for processing.
`Field name provided, Name is not an External ID or indexed field for Account`	The field used to define the relationship is not an indexed or External ID field.	Use an indexed or External ID field when referencing relationships. `idLookup` fields are only supported if the referenced field is the same object type as the parent. Otherwise, use a field explicitly marked as an External Id.

Limitations

Be sure to review the following information.

For connector limitations, see Salesforce Bulk API 2.0 Sink Connector limitations. For additional information, see Considerations.
If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.

Quick Start

Use this quick start to get up and running with the Salesforce Bulk API 2.0 Sink connector. The quick start provides the basics of selecting the connector and configuring it to capture records and record changes from Kafka topics.

Prerequisites

Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
Salesforce account credentials.
The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.
Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
At least one topic must exist in your Confluent Cloud cluster before creating the connector.
For networking considerations, see Networking and DNS. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.

Kafka cluster credentials. The following lists the different ways you can provide credentials.
- Enter an existing service account resource ID.
- Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.
- Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster

To create and launch a Kafka cluster in Confluent Cloud, see Create a kafka cluster in Confluent Cloud.

Step 2: Add a connector

In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector

Click the Salesforce Bulk API 2.0 Sink connector card.

Important

At least one topic must exist in your Confluent Cloud cluster before creating the connector.

Step 4: Enter the connector details

Note

Make sure you have all your prerequisites completed.
An asterisk ( * ) designates a required entry.

At the Add Salesforce Bulk API 2.0 Sink Connector screen, complete the following:

Select a topic

Select the topic you want to send data to from the Topics list. To create a new topic, click +Add new topic.

Kafka credentials

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. 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.
Click Continue.

Authentication

Configure the authentication properties:
- Salesforce grant type: Sets the authentication grant type to PASSWORD , JWT_BEARER (Salesforce JSON Web Token (JWT)) or CLIENT_CREDENTIALS. Defaults to PASSWORD.
Salesforce details
- Salesforce instance: The URL of the Salesforce endpoint to use. The default is https://login.salesforce.com. This directs the connector to use the endpoint specified in the authentication response.
- Salesforce username: The Salesforce username for the connector to use.
- Salesforce password: The Salesforce password for the connector to use.
- Salesforce password token: The Salesforce security token associated with the username.
- Salesforce consumer key: The consumer key for the OAuth application.
- Salesforce consumer secret: The consumer secret for the OAuth application.
- Salesforce JWT keystore file: If using the grant type JWT_BEARER, upload the JWT keystore file.
- Salesforce JWT keystore password: The password used to access the JWT keystore file.
Note
The following properties are used based on the Salesforce grant type you choose.
- JWT_BEARER: Requires username, consumer key, JWT keystore file, and JWT keystore password.
- PASSWORD: Requires username, password, password token, consumer key, and consumer secret.
- CLIENT_CREDENTIALS: Requires consumer key, consumer secret (client ID and client secret of a Salesforce connected application) and Salesforce domain URL in Salesforce instance option. The default value https://login.salesforce.com does not work for this option. To use CLIENT_CREDENTIALS, you must enable the Client Credentials flow in your connected Salesforce application and assign an integration user.
Click Continue.

Configuration

Input Kafka record value format: Select the input Kafka record value format (data coming from the Kafka topic). Valid values are AVRO, JSON_SR (JSON Schema), or PROTOBUF. A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
Number of Salesforce Objects: Number of Salesforce Objects to write to. It must be between 1 and 5.

Object 1 configuration

Salesforce SObject1 Name: Specifies the Salesforce SObject1 to write to.
Salesforce SObject1 Topics: A comma-separated list of topics associated with Salesforce SObject1.
SObject1 Override Event Type: Determines whether to override the SObject1 EventType(create, update, delete) with the configured sink operation.
SObject1 Sink Operation: The Salesforce sink operation to perform for SObject1 if an override is enabled.
SObject1 Ignore Fields: A comma-separated list of fields to ignore when pushing SObject1 records.
SObject1 Ignore Reference Fields: Prevents reference-type fields from being updated or inserted for SObject1.
SObject1 Use Custom ID Field: Determines whether to use a custom external ID field for SObject1 insert or upsert operations.
SObject1 Custom ID Field Name: Specifies the custom external ID field name for SObject1.
Skip SObject1 Relationship Fields: Prevents relationship fields in records from being updated or inserted in Salesforce SObjects.

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.

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?.
Behavior on API errors: How the connector behaves when a Salesforce API error occurs. Valid options are fail and ignore (the default). If set to fail, the connector stops.
Max timeout milliseconds: The maximum time in milliseconds (ms) that the connector waits for all batch operations to complete. Defaults to 200000 ms.

Additional Configs

Value Converter Schema ID Deserializer: The class name of the schema ID deserializer for values. This is used to deserialize schema IDs from the message headers.
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.
Schema ID For Value Converter: The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This is used 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.
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.
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.
Key Converter Schema ID Deserializer: The class name of the schema ID deserializer for keys. This is used to deserialize schema IDs from the message headers.
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.
Schema GUID For Key Converter: The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This is used 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.
Schema GUID For Value Converter: The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This is used 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.
Value Converter Connect Meta Data: Allow the Connect converter to add its metadata to the output schema. Applicable for 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: How to construct the subject name for key schema registration.
Schema ID For Key Converter: The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This is used 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.

Auto-restart policy

Enable Connector Auto-restart: Control 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. In such cases, you would need to manually restart the connector.

Consumer configuration

Max poll interval(ms): Set 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: Set 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.

Connection details

Max Retry Time in Milliseconds: In case of error when making a request to Salesforce, the connector will retry until this time (in ms) elapses. The default value is 30000 (30 seconds). Minimum value is 1 sec

Salesforce details

Salesforce Version: The version of the Salesforce API to use. Defaults to latest.

Transforms

Single Message Transforms: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.

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.

For all property values and definitions, see Configuration Properties.

Click Continue.

Sizing

The connector supports running one or more tasks. More tasks may improve performance (that is, consumer lag is reduced with multiple tasks running).

Click Continue.

Review and Launch

Verify the connection details by previewing the running configuration.
After you’ve validated that the properties are configured to your satisfaction, click Launch.
The status for the connector should go from Provisioning to Running.

Step 5: Check for records

Verify that records are being produced at the endpoint. For additional information, see Considerations.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Using the Confluent CLI

Complete the following steps to set up and run the connector using the Confluent CLI.

Important

Make sure you have all your prerequisites completed.

Step 1: List the available connectors

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: List the connector configuration properties

Enter the following command to show the connector configuration properties:

confluent connect plugin describe <connector-plugin-name>

The command output shows the required and optional configuration properties.

Step 3: Create the connector configuration file

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties for a single SObject.

{
  "connector.class": "SalesforceBulkApiV2Sink",
  "name": "SalesforceBulkApiV2Sink_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key>",
  "kafka.api.secret": "<my-kafka-api-secret>",
  "topics": "TestBulkAPI",
  "input.data.format": "AVRO",
  "salesforce.grant.type": "PASSWORD",
  "salesforce.instance": "https://login.salesforce.com",
  "salesforce.username": "<my-username>",
  "salesforce.password": "**************",
  "salesforce.password.token": "************************",
  "salesforce.consumer.key": "**************",
  "salesforce.consumer.secret": "************************",
  "salesforce.object.num": "1",
  "salesforce.object1": "<salesforce-Object1>",
  "tasks.max": "1"
}

Note the following property definitions:

"connector.class": Identifies the connector plugin name.
"name": Sets a name for your new connector.

"kafka.auth.mode": Identifies the connector authentication mode you want to use. There are two options: SERVICE_ACCOUNT or KAFKA_API_KEY (the default). To use an API key and secret, specify the configuration properties kafka.api.key and kafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the property kafka.service.account.id=<service-account-resource-ID>. To list the available service account resource IDs, use the following command:
```
confluent iam service-account list
```
For example:
```
confluent iam service-account list

   Id     | Resource ID |       Name        |    Description
+---------+-------------+-------------------+-------------------
   123456 | sa-l1r23m   | sa-1              | Service account 1
   789101 | sa-l4d56p   | sa-2              | Service account 2
```

""topics": Enter a Kafka topic name or a comma-separated list of topics. A topic must exist before launching the connector.
"input.data.format": Sets the input data format (data coming from the Kafka topic): AVRO, JSON_SR (JSON Schema), or PROTOBUF. A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
"salesforce.grant.type": Sets the authentication grant type to PASSWORD (username+password) , JWT_BEARER (Salesforce JSON Web Token (JWT)) or CLIENT_CREDENTIALS. Defaults to PASSWORD.
Note
The following properties are used based on the Salesforce grant type you choose.
- JWT_BEARER: Requires username, consumer key, JWT keystore file, and JWT keystore password.
- PASSWORD: Requires username, password, password token, consumer key, and consumer secret.
- CLIENT_CREDENTIALS: Requires consumer key, consumer secret (client ID and client secret of a Salesforce connected application) and Salesforce domain URL in Salesforce instance option. The default value https://login.salesforce.com does not work for this option. To use CLIENT_CREDENTIALS, you must enable the Client Credentials flow in your connected Salesforce application and assign an integration user.
"salesforce.username": The Salesforce username for the connector to use.
"salesforce.password": The Salesforce username password.
"salesforce.password.token": The Salesforce security token associated with the username.
"salesforce.consumer.key": The consumer key for the OAuth application.
"salesforce.consumer.secret": The consumer secret for the OAuth application.
"salesforce.jwt.keystore.file": Salesforce JWT keystore file. The JWT keystore file is a binary file and you supply the contents of the file in the property encoded in Base64. To use the salesforce.jwt.keystore.file property, encode the keystore contents in Base64, take the encoded string, add the data:text/plain:base64 prefix, and then use the entire string as the property entry. For example:
```
"salesforce.jwt.keystore.file" : "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAGY2xpZ...==",
"salesforce.jwt.keystore.password" : "<password>",
```
"salesforce.jwt.keystore.password": Enter the password used to access the JWT keystore file.
"salesforce.object1": Enter the Object1 name to write to.
"tasks.max": Enter the number of tasks in use by the connector. Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").

Note

To enable CSFLE or CSPE for data encryption, specify the following properties:

csfle.enabled: Flag to indicate whether the connector honors CSFLE or CSPE rules.
sr.service.account.id: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.
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.

The following example shows the required connector properties for two SObjects:

{
  "connector.class": "SalesforceBulkApiV2Sink",
  "input.data.format": "AVRO",
  "name": "SalesforceBulkApiV2Sink_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key>",
  "kafka.api.secret": "<my-kafka-api-secret>",
  "salesforce.grant.type": "PASSWORD",
  "salesforce.instance": "https://login.salesforce.com",
  "salesforce.username": "<username>",
  "salesforce.password": "<password>",
  "salesforce.password.token": "<password-token>",
  "salesforce.consumer.key": "<consumer-key>",
  "salesforce.consumer.secret": "<consumer-secret>",
  "salesforce.object.num": "2",
  "salesforce.object1": "<salesforce-Object1>",
  "salesforce.object1.topics": "<salesforce-Object1-topic-list>",
  "salesforce.object2": "<salesforce-Object2>",
  "salesforce.object2.topics": "<salesforce-Object2-topic-list>",
  "tasks.max": "1"
}

Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.

For all property values and description, see Configuration Properties. For additional information, see Considerations.

Step 4: Load the properties file and create the connector

Enter the following command to load the configuration and start the connector:

confluent connect cluster create --config-file <file-name>.json

For example:

confluent connect cluster create --config-file salesforce-bulk-api-v2-sink.json

Example output:

Created connector SalesforceBulkApiV2Sink_0 lcc-aj3qr

Step 5: Check the connector status

Enter the following command to check the connector status:

confluent connect cluster list

Example output:

ID          |            Name              | Status  |  Type
+-----------+------------------------------+---------+-------+
lcc-aj3qr   | SalesforceBulkApiV2Sink_0    | RUNNING | sink

Step 6: Check Check for records.

Verify that records are being produced at the endpoint. For additional information, see Considerations.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Configuration Properties

Use the following configuration properties with the fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors for Confluent Platform.

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

reporter.result.topic.name

The name of the topic to produce records to after successfully processing a sink record. Defaults to ‘success-${connector}’ if not set. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

Type: string
Default: success-${connector}
Importance: low

reporter.error.topic.name

The name of the topic to produce records to after each unsuccessful record sink attempt. Defaults to ‘error-${connector}’ if not set. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

Type: string
Default: error-${connector}
Importance: low

Schema Config

schema.context.name

Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.

Type: string
Default: default
Importance: medium

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR and PROTOBUF. Note that you need to have Confluent Cloud Schema Registry configured

Type: string
Importance: high

How should we connect to your data?

name

Sets a name for your connector.

Type: string
Valid Values: A string at most 64 characters long
Importance: high

Kafka Cluster credentials

kafka.auth.mode

Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode, whenever possible.

Type: string
Valid Values: SERVICE_ACCOUNT, KAFKA_API_KEY
Importance: high

kafka.api.key

Kafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.

Type: password
Importance: high

kafka.service.account.id

The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.

Type: string
Importance: high

kafka.api.secret

Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.

Type: password
Importance: high

How should we connect to Salesforce?

salesforce.grant.type

Salesforce grant type. Valid options are ‘PASSWORD’, ‘CLIENT_CREDENTIALS’ and ‘JWT_BEARER’.

Type: string
Default: PASSWORD
Importance: high

salesforce.instance

The URL of the Salesforce endpoint to use. When using ‘CLIENT_CREDENTIALS’ grant type, provide your Salesforce domain URL. The default is https://login.salesforce.com, which directs the connector to use the endpoint specified in the authentication response.

Type: string
Default: https://login.salesforce.com
Importance: high

salesforce.username

The Salesforce username the connector should use.

Type: string
Importance: high

salesforce.password

The Salesforce password the connector should use.

Type: password
Importance: high

salesforce.password.token

The Salesforce security token associated with the username.

Type: password
Importance: high

salesforce.consumer.key

The client id(consumer key) for the Salesforce Connected app.

Type: password
Importance: high

salesforce.consumer.secret

The client secret(consumer secret) for the Salesforce Connected app.

Type: password
Importance: medium

salesforce.jwt.keystore.file

Salesforce JWT keystore file which contains the private key.

Type: password
Default: [hidden]
Importance: medium

salesforce.jwt.keystore.password

Password used to access JWT keystore file.

Type: password
Importance: medium

salesforce.object.num

Number of Salesforce Objects to write to. Must be between 1 and 5.

Type: int
Default: 1
Valid Values: [1,…,5]
Importance: high

salesforce.version

The version of Salesforce API to use.

Type: string
Default: 65.0
Importance: low

Object 1 configuration

salesforce.object1

The Salesforce SObject1 to write to.

Type: string
Importance: high

salesforce.object1.topics

Comma separated list of topics associated with Salesforce SObject1

Type: list
Default: “”
Importance: high

salesforce.object1.override.event.type

Override SObject1 EventType(create, update, delete) with the configured sink operation.

Type: boolean
Default: false
Importance: low

salesforce.object1.sink.object.operation

The Salesforce sink operation to perform for SObject1 when override is enabled.

Type: string
Default: insert
Importance: low

salesforce.object1.ignore.fields

Comma separated list of fields to ignore when pushing a record for SObject1.

Type: list
Default: “”
Importance: low

salesforce.object1.ignore.reference.fields

Prevent reference-type fields from being updated or inserted for SObject1.

Type: boolean
Default: false
Importance: low

salesforce.object1.use.custom.id.field

Use a custom external ID field for SObject1 insert/upsert operations.

Type: boolean
Default: false
Importance: low

salesforce.object1.custom.id.field.name

The custom external ID field name for SObject1.

Type: string
Default: “”
Importance: low

skip.object1.relationship.fields

Flag to skip relationship fields in records from being updated or inserted in Salesforce SObjects.

Type: boolean
Default: true
Importance: medium

Connection details

behavior.on.api.errors

Error handling behavior config for any API errors.

Type: string
Default: ignore
Importance: low

request.max.retries.time.ms

In case of error when making a request to Salesforce, the connector will retry until this time (in ms) elapses. The default value is 30000 (30 seconds). Minimum value is 1 sec

Type: long
Default: 30000 (30 seconds)
Valid Values: [1000,…,250000]
Importance: low

max.timeout.ms

The maximum timeout in milliseconds that the connector will continue waiting for the completion of all batch operations.

Type: long
Default: 200000 (200 seconds)
Importance: low

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

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

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

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.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

Considerations

Note the following when using this connector.

Unexpected errors

When the connector is performing operations on Salesforce SObjects, unexpected errors can occur that will be reported. The following lists several reasons why errors may occur:

Attempting to insert a duplicate record. Rules for determining duplicates are configurable in Salesforce.
Attempting to delete, update, or upsert a record that does not exist because the Id field does not match.
Attempting an operation on a field where the Id field value matches a previously deleted Id field value.

ID field semantics

When the Salesforce Bulk API Sink connector consumes records on Kafka topics which originated from the Salesforce PushTopic Source connector, an Id field is included that is a sibling of the other fields in the body of the SObject. Note that the Id is only valid within the Salesforce organization from which the record was streamed. For upsert, delete, and update operations, attempting to rely on this Id field causes failures when used on different Salesforce organizations. Inserts always ignore the Id field because Id fields are internally fully-managed in Salesforce. Upsert operations must be used with the external ID configuration properties salesforce.use.custom.id.field=true and salesforce.custom.id.field.name=<externalIdField>.

Caution

For update and delete operations across Salesforce organizations, an external ID must be configured in Salesforce. Also, a custom ID must always be marked as an external ID across both organizations.

Input topic record format

The input topic record format is expected to be the same as the record format written to output topics by the Salesforce PushTopic Source connector. The Kafka key value is not required.

Read-Only fields

Salesforce SObject fields may not be writable by insert, update, or upsert operation because the fields are set with creatable=false or updatable=false attributes within Salesforce. If a write is attempted to a field with these attributes set, the sink connector excludes the field in the operation rather than fail the entire operation. This behavior is not configurable.

Event Type

The Salesforce Bulk API sink connector Kafka record format contains an _EventType field. This field describes the type of PushTopic event that generated the record, if the record was created by the Salesforce PushTopic Source connector. Types are created, updated, and deleted. When processing records, the sink connector (by default) maps the _EventType to either an insert, update, or delete operation on the configured SObject. This behavior can be overridden using the override.event.type=true and salesforce.sink.object.operation=<sink operation> fields. Overriding the event type ignores the _EventType field in the record and obeys the salesforce.sink.object.operation for every record.

API Limits

The Salesforce Bulk API sink connector is limited by number of batches to execute, records per batch, and length of the batch. For detailed limitations, see Bulk API Limits.
The Salesforce Bulk API supports upsert operations only when used with the external ID configuration properties salesforce.use.custom.id.field=true and salesforce.custom.id.field.name=<externalIdField>.

Frequently asked questions

Find answers to frequently asked questions about the Salesforce Bulk API 2.0 Sink connector for Confluent Cloud.

Authentication and connection

What authentication methods are supported, and how do I configure `CLIENT_CREDENTIALS` grant type?

The connector supports three authentication grant types:

PASSWORD (username + password + security token): Default authentication method
JWT_BEARER (JSON Web Token): Certificate-based authentication
CLIENT_CREDENTIALS (OAuth 2.0): Machine-to-machine authentication

For CLIENT_CREDENTIALS authentication:

You must use your Salesforce my domain URL (for example, https://mycompany.my.salesforce.com) in the salesforce.instance configuration. The default https://login.salesforce.com URL will not work.
Enable Client Credentials Flow in your Salesforce Connected App settings.
Configure a Run As user (execution user) in the Connected App policies. Without this, authentication fails with an invalid_grant error.
Ensure the execution user has the necessary permissions and profiles assigned.

For more information, see Step 4: Enter the connector details.

Why am I getting “Connection pool shut down” errors?

This error typically occurs during connector restarts or when the connector is shutting down:

java.lang.IllegalStateException: Connection pool shut down
at io.confluent.connect.salesforce.bulk.v2.SalesforceBulkApiV2SinkTask.tryBatch

The error indicates that the connector attempted to execute a Bulk API operation while the HTTP connection pool was being shut down. This is usually a transient error that occurs during:

Connector restarts (manual or automatic).
Configuration updates that require task restarts.
Platform maintenance windows.

Resolution:

The connector will automatically recover after the restart completes.
If the error persists after multiple restarts, check connector logs for underlying authentication or network issues.
Verify that your Salesforce credentials are valid and not expired.

Data format and schema issues

Why am I getting `Bad Kafka SinkRecord. Value is not of type Struct` errors?

This error occurs when the connector encounters tombstone records (null values) or records that are not in the expected Struct format:

org.apache.kafka.connect.errors.ConnectException: Bad Kafka SinkRecord.
Value is not of type Struct. Kafka topics are not in the format the connector is expecting.

The Salesforce Bulk API 2.0 Sink connector requires all records to be in Struct format and does not handle tombstone records by default.

Resolution:

Use the Tombstone Handler SMT: Add the io.confluent.connect.transforms.TombstoneHandler Single Message Transform to filter out tombstone records. For more information, see /platform/current/TombstoneHandler <connect/transforms/tombstonehandler.html>.
Verify data format: Ensure your topic data is in Avro, JSON Schema (JSON_SR), or Protobuf format with a valid schema registered in Confluent Cloud Schema Registry.
Check Schema Registry: Confirm that Confluent Cloud Schema Registry is enabled and contains valid schemas for your topics.

Example configuration with Tombstone Handler:

{
  "transforms": "TombstoneHandler",
  "transforms.TombstoneHandler.type": "io.confluent.connect.transforms.TombstoneHandler"
}

Why are some fields missing after I updated my Salesforce object definition?

When you add new fields to a Salesforce object, the connector may not immediately recognize them. The connector caches the Salesforce object metadata when it connects.

To ensure the connector processes new fields:

Restart the connector: This refreshes the cached Salesforce object metadata and ensures the connector recognizes newly added fields.
Verify field visibility: Ensure the Salesforce user has field-level security permissions to access the new fields.
Check success topic: Review messages in the success reporter topic to confirm all expected fields are being processed.

Note

The connector does not automatically detect schema changes. You must manually restart the connector after modifying the Salesforce object definition.

Batching and performance tuning

How do I control batch size to avoid exceeding Salesforce daily batch limits?

Salesforce enforces a strict daily limit of 15,000 batches per 24 hours for Bulk API 2.0 operations. By default, the connector may create many small batches, which can quickly exhaust this limit.

To optimize batching and reduce the number of batches created:

Configure consumer override properties:

The following properties control how many records are fetched from Kafka and batched together before sending to Salesforce:

consumer.override.max.poll.records: Maximum number of records fetched in a single poll (default: 500). Increase this to batch more records together.
consumer.override.fetch.min.bytes: Minimum bytes of data to fetch per request (default: 1 byte). Increase this to wait for more data before creating a batch.
consumer.override.max.poll.interval.ms: Maximum time between polls (default: 300000 ms / 5 minutes). Increase if processing large batches takes longer.

Example configuration for large batches:

{
  "consumer.override.max.poll.records": "50000",
  "consumer.override.fetch.min.bytes": "512000",
  "consumer.override.max.poll.interval.ms": "600000"
}

Important considerations:

The maximum batch size for Salesforce Bulk API 2.0 is 150 MB (with base64 encoding).
If your topic contains duplicate external IDs within a batch, the connector splits the batch to comply with Salesforce’s requirement that external IDs must be unique within a batch.
Larger batches reduce the number of API calls but may increase processing time per batch.

For more information, see Salesforce Bulk API Limits.

Note

The consumer.override properties are advanced configurations. Contact Confluent Support if you need assistance configuring these settings for your environment.

Why does the connector create multiple small batches instead of one large batch?

The connector may split records into multiple batches for several reasons:

Duplicate external IDs: Salesforce Bulk API 2.0 does not allow duplicate external ID values within the same batch. When the connector detects duplicate external IDs in the polled records, it automatically creates separate batches.
Batch size limits: Salesforce limits each batch to 150 MB. If the polled records exceed this size, the connector splits them into multiple batches.
Operation type differences: Records with different operation types (insert, update, upsert, delete) are batched separately.
Object type differences: When using multiple SObjects, records for different objects are batched separately.

To minimize batch creation:

Ensure records in your Kafka topic have unique external ID values when using upsert operations.
Increase consumer.override.max.poll.records and consumer.override.fetch.min.bytes to fetch more records per poll.
Consider using a single operation type per connector instance.

How can I monitor Salesforce API usage to avoid hitting batch limits?

To monitor your Salesforce API and batch usage:

Salesforce Setup Console: Navigate to Setup > System Overview > API Usage in your Salesforce org to view current API and Bulk API usage.
Success and Error Topics: Monitor the connector’s success and error reporter topics to track how many batches are being created and their success rate.
Connector Metrics: Use Confluent Cloud metrics to monitor connector throughput, lag, and error rates.
Salesforce Event Monitoring: Enable Event Monitoring in Salesforce (Enterprise Edition and above) to track API usage patterns.

If you consistently approach the 15,000 batch limit:

Optimize batching configuration as described in the batching FAQ above.
Distribute workload across multiple Salesforce organizations if possible.
Consider using multiple Salesforce user accounts to distribute API usage.

SObject operations and configuration

Can I configure multiple SObjects in one connector?

Yes, the connector supports configuring up to five SObjects in a single connector instance.

To configure multiple SObjects:

Set Salesforce SObject Number (salesforce.object.num) to the number of SObjects (1-5).
For each SObject, provide:
- The SObject name (salesforce.object<N>).
- A comma-separated list of associated topics (salesforce.object<N>.topics).
- Optional: SObject-specific configurations like salesforce.object<N>.sink.operation.
Each topic must be mapped to exactly one SObject. A topic cannot contain records for multiple SObjects.

Example configuration for two SObjects:

{
  "salesforce.object.num": "2",
  "salesforce.object1": "Account",
  "salesforce.object1.topics": "account-topic",
  "salesforce.object1.sink.operation": "upsert",
  "salesforce.object2": "Contact",
  "salesforce.object2.topics": "contact-topic",
  "salesforce.object2.sink.operation": "insert"
}

This feature allows you to reduce operational overhead and costs by consolidating multiple low-throughput SObjects into a single connector instance.

Does the connector support Salesforce Big Objects?

No, the Salesforce Bulk API 2.0 Sink connector currently does not support big Objects (custom objects ending with __b).

Big Objects have different API requirements and limitations compared to standard SObjects:

They use a different indexing mechanism (composite indexes instead of standard IDs).
They only support Bulk API Query and Insert operations.
They do not support standard Salesforce IDs.

If you need to write to big Objects, you will need to use custom integration methods or wait for future connector support.

How do I configure the connector to handle relationship fields?

The Salesforce Bulk API 2.0 Sink connector supports relationship fields (lookup and master-detail relationships) using the skip.objectN.relationship.fields configuration property.

Default behavior (skip.objectN.relationship.fields=true):

Relationship fields are filtered out and not sent to Salesforce. This is the default behavior for backward compatibility.

Enable relationship fields (skip.objectN.relationship.fields=false):

Set sskip.objectN.relationship.fields=false to process relationship fields in your records. Relationship fields must follow Salesforce’s external ID format (for example, ParentObject__r.ExternalId__c).

Example configuration:

{
  "skip.objectN.relationship.fields": "false"
}

Important considerations:

Relationship fields must reference the external ID of the related object (for example, Account__r.AccountNumber__c), not the Salesforce internal ID.
The related object must exist in Salesforce before the relationship can be established.
The connector currently does not support the format SomeObject__r.ExternalId__c for referential fields in all scenarios. Contact Confluent Support if you encounter issues.

For more information about Salesforce relationship fields, see Salesforce Relationship Fields documentation.

Error handling and troubleshooting

Why is the success reporter topic not receiving messages?

The connector writes success and error records to reporter topics. If the success topic is not receiving messages, several issues may be occurring:

Common causes:

CSV record mapping failure: The connector failed to map Salesforce API responses back to the original Kafka records. This can happen when special characters or formatting in CSV data causes mismatches.
You may see this log message:
```
failed to map API response to sink record. We will miss reporting record to success topic.
```
CSV data normalization: Salesforce Bulk API may normalize certain values (for example, #N/A literals) which prevents the connector from matching responses to original records.
Schema mismatches: If the Salesforce object schema changed, the connector may fail to properly process success responses.

Resolution:

Check connector logs: Look for warnings about mapping failures or CSV processing errors.
Verify CSV formatting: Ensure your Kafka records do not contain special CSV characters that could cause parsing issues.
Restart the connector: A connector restart may resolve transient mapping issues.
Review field values: Avoid using special literals like #N/A in field values that could be normalized by Salesforce.

If the issue persists, contact Confluent Support with your connector ID and sample records that are failing to map.

What should I do if the connector fails with `Index out of bounds` errors?

Index out of bounds errors can occur due to internal processing issues with CSV batch handling:

java.lang.IndexOutOfBoundsException: Index: X, Size: Y

This is typically a transient error that may occur during:

Processing of malformed CSV data.
Handling of Salesforce API responses with unexpected formats.
Internal state inconsistencies during batch processing.

Resolution:

Restart the connector: The connector should recover automatically after restart.
Check for schema changes: Verify that the Salesforce object schema matches the connector’s expectations.
Review recent data: Check if recently produced records have any unusual formatting or values.
Contact support: If the error persists after restart, contact Confluent Support with the connector ID and error logs.

API limits and Salesforce quotas

What are the Salesforce API limits for Bulk API 2.0?

Salesforce enforces several limits on Bulk API 2.0 operations that can affect the connector:

Daily batch limit: Maximum of 15,000 batches per 24-hour rolling window per Salesforce organization.
Job data size: Maximum of 100 MB per batch (with base64 encoding).
Concurrent jobs: Salesforce limits the number of concurrent Bulk API jobs that can run simultaneously.
API request limits: General API request limits apply to authentication and metadata operations.

To monitor your Salesforce API usage:

Navigate to Setup > System Overview > API Usage in your Salesforce organization.
Review current API consumption and remaining daily limits.
Set up alerts in Salesforce to notify you when approaching limits.

For detailed information, see Salesforce Bulk API Limits and Salesforce Bulk API 2.0 Sink Connector.

What happens when I exceed Salesforce API limits?

If you exceed Salesforce API limits:

Connector failure: The connector fails with an error indicating which limit was exceeded.
Automatic retry: The connector uses ExponentialBackOff for retry with request.max.retries.time.ms configuration. After the retry time expires, the task is marked as failed.
Data backlog: Records accumulate in the Kafka topic, increasing consumer lag.

To prevent exceeding limits:

Optimize batching configuration to reduce the number of batches created.
Monitor API usage regularly in the Salesforce Setup console.
Distribute workload across multiple Salesforce organizations if possible.
Use multiple Salesforce user accounts to distribute API quota.

Next Steps

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud for Apache Flink, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.

Salesforce Bulk API 2.0 Sink Connector for Confluent Cloud

Features

Salesforce relationship fields

Prerequisites

Process relationship fields

Enable relationship field

Associated Avro schema for sink topic

Sample sink record

Common issues and resolutions

Limitations

Quick Start

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster

Step 2: Add a connector

Step 3: Select your connector

Step 4: Enter the connector details

Step 5: Check for records

Using the Confluent CLI

Step 1: List the available connectors

Step 2: List the connector configuration properties

Step 3: Create the connector configuration file

Step 4: Load the properties file and create the connector

Step 5: Check the connector status

Step 6: Check Check for records.

Configuration Properties

Which topics do you want to get data from?

Schema Config

Input messages

How should we connect to your data?

Kafka Cluster credentials

How should we connect to Salesforce?

Object 1 configuration

Connection details

Consumer configuration

Number of tasks for this connector

Additional Configs

Auto-restart policy

Considerations

Unexpected errors

ID field semantics

Input topic record format

Read-Only fields

Event Type

API Limits

Frequently asked questions

Authentication and connection

What authentication methods are supported, and how do I configure CLIENT_CREDENTIALS grant type?

Why am I getting “Connection pool shut down” errors?

Data format and schema issues

Why am I getting Bad Kafka SinkRecord. Value is not of type Struct errors?

Why are some fields missing after I updated my Salesforce object definition?

Batching and performance tuning

How do I control batch size to avoid exceeding Salesforce daily batch limits?

Why does the connector create multiple small batches instead of one large batch?

How can I monitor Salesforce API usage to avoid hitting batch limits?

SObject operations and configuration

Can I configure multiple SObjects in one connector?

Does the connector support Salesforce Big Objects?

How do I configure the connector to handle relationship fields?

Error handling and troubleshooting

Why is the success reporter topic not receiving messages?

What should I do if the connector fails with Index out of bounds errors?

API limits and Salesforce quotas

What are the Salesforce API limits for Bulk API 2.0?

What happens when I exceed Salesforce API limits?

Next Steps

What authentication methods are supported, and how do I configure `CLIENT_CREDENTIALS` grant type?

Why am I getting `Bad Kafka SinkRecord. Value is not of type Struct` errors?

What should I do if the connector fails with `Index out of bounds` errors?