# Getting Started with Confluent Cloud (Custom Connect)

This guide shows how to use the SingleStore Kafka Sink connector ("the connector") as a custom connector to integrate with Confluent Cloud and connect to your SingleStore deployments.

SingleStore recommends having hands-on experience with Confluent Cloud and an understanding of its concepts. Refer to [Custom Connector for Confluent Cloud Quick Start](https://docs.confluent.io/cloud/current/connectors/bring-your-connector/custom-connector-qs.html#custom-connector-for-ccloud-quick-start) for related information.

## Prerequisites

* An active SingleStore deployment.
* Access to a [Confluent Cloud](https://www.confluent.io/confluent-cloud/) cluster.

## Configure the Connection

To connect to your SingleStore deployment from Confluent Cloud using the SingleStore Kafka Sink connector, perform the following tasks:

1. Download the `singlestore-singlestore-kafka-connector-<version>.zip` file from the [SingleStore Kafka Connector](https://github.com/memsql/singlestore-kafka-connector/releases/latest/) GitHub repository.

2. Update the firewall configuration of your SingleStore deployment to allow access to Confluent Cloud.

   1. On the [Cloud Portal](https://portal.singlestore.com), select **\<your\_SingleStore\_deployment> > Firewall**.

   2. Under **Inbound**, select **Edit**.

   3. Either specify the inbound IP addresses to allow or select **Allow access from anywhere** to allow access from any IP address.

   4. Select **Save**.

3. Launch a Confluent Cloud cluster. Refer to [Quick Start for Confluent Cloud](https://docs.confluent.io/cloud/current/get-started/index.html#cloud-quickstart) for more information.

4. Create a topic.

   1. On the Confluent dashboard, select **Topics > Add topic**.

   2. On the **New topic** page, enter a name for the topic and the number of partitions.

   3. Select **Create with defaults > Skip**.

5. Add a custom connector plugin.

   1. On the Confluent dashboard, select **Connectors > Add plugin**.

   2. On the **Add Custom Connector Plugin** page, enter or select the following information:

      1. **Connector plugin name**: Enter **SingleStore Kafka Sink**.

      2. **Connector class**: Enter `com.singlestore.kafka.SingleStoreSinkConnector`.

      3. **Connector type:** Select **Sink**.

      4. **Connector archive**: Select the SingleStore Kafka Sink connector archive downloaded earlier.

      5. **Sensitive properties**: Specify `connection.password` to mask the password.

   3. Agree to the disclaimer.

   4. Select **Submit**. The SingleStore Kafka Sink connector is now available under Connector Plugins.

6. On the **Connector Plugins** page, select **SingleStore Kafka Sink**.

7. On the **Add SingleStore Kafka Sink connector** page, enter the following information:

   1. Under **Kafka Credentials**, specify the method used to provide the connection credentials. Select one of the following:

      1. **My account**: Allows the connector to globally access everything that the user's account can access. With a user account, the connector uses an API key and secret to access the Kafka cluster. SingleStore does not recommend this option for production environments.

      2. **Service account**: Provides limited access to the connector by using a [service account](https://docs.confluent.io/cloud/current/connectors/service-account.html#s3-cloud-service-account). SingleStore recommends this option for production environments.

      3. **Use an existing API key**: Allows access to the Kafka cluster via an API key and secret. SingleStore does not recommend this option for production environments.

   2. Select **Continue**.

   3. Under **Configuration**, enter the following connection configuration details in key-value pairs:
      | **Key**                                          | **Value**                                                              |
      | ------------------------------------------------ | ---------------------------------------------------------------------- |
      | `connection.ddlEndpoint``connection.dmlEndpoint` | IP address or hostname of theSingleStoredeployment.                    |
      | `connection.database`                            | Name of theSingleStoredatabase to connect with.                        |
      | `connection.user`                                | Name of theSingleStoredatabase user with which to access the database. |
      | `connection.password`                            | Password for theSingleStoredatabase user.                              |
      | `topics`                                         | List of Kafka topics.                                                  |
      | `value.converter`                                | Set to`org.apache.kafka.connect.json.JsonConverter`.                   |
      | `value.converter.schemas.enable`                 | Set to`true`.                                                          |
      Refer to [SingleStore Kafka Sink Connector Properties](https://docs.singlestore.com/db/v9.1/load-data/integrate-with-singlestore/singlestore-kafka-sink-connector/singlestore-kafka-sink-connector-properties.md) for more information.

   4. Select **Continue**.

   5. Under **Networking**, whitelist the SingleStore deployment endpoint. Specify the endpoint in the `<hostname>:<port>:TCP` format.

   6. Select **Continue > Continue** (Sizing step) **> Continue** (Review and launch step).

8. Add data to the Kafka topic created earlier.

   1. Select **Topics > \<your\_Kafka\_Topic> > Messages > Produce new message**. This example uses a Kafka topic named **SingleStore-quickstart**.

   2. On the **Produce a new message** dialog, add a message. In this example, the following are added:
      | **Key**   | `1`                                                                                                                                                                                                                                                                                                                                            |
      | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
      | **Value** | `{"schema": {"type": "struct", "optional": false, "version": 1, "fields": [{ "field": "Id", "type": "string", "optional": true }, { "field": "Artist", "type": "string", "optional": true }, { "field": "Song", "type": "string", "optional": true }] }, "payload": { "Id": "1", "Artist": "Rick Astley", "Song": "Never Gonna Give You Up"}}` |

   3. Select **Produce**. The data is added to a SingleStore table named `SingleStore-quickstart`, in the specified database.

9. Log in to your SingleStore deployment and run the following command to verify that the data has been ingested.
   ```sql
   SELECT * FROM `SingleStore-quickstart`;

   ```
   ```output

   +------+-------------+-------------------------+
   | Id   | Artist      | Song                    |
   +------+-------------+-------------------------+
   | 1    | Rick Astley | Never Gonna Give You Up |
   +------+-------------+-------------------------+
   ```

***

Modified at: August 3, 2025

Source: [/db/v9.1/load-data/integrate-with-singlestore/singlestore-kafka-sink-connector/getting-started-with-confluent-cloud-custom-connect/](https://docs.singlestore.com/db/v9.1/load-data/integrate-with-singlestore/singlestore-kafka-sink-connector/getting-started-with-confluent-cloud-custom-connect/)

(An index of the documentation is available at /llms.txt)