landing_page/qdrant-landing/content/documentation/data-management/confluent.md

---
title: Confluent Kafka
aliases: [ ../frameworks/confluent/ ]
---

![Confluent Logo](/documentation/frameworks/confluent/confluent-logo.png)

Built by the original creators of Apache Kafka®, [Confluent Cloud](https://www.confluent.io/confluent-cloud/?utm_campaign=tm.pmm_cd.cwc_partner_Qdrant_generic&utm_source=Qdrant&utm_medium=partnerref) is a cloud-native and complete data streaming platform available on AWS, Azure, and Google Cloud. The platform includes a fully managed, elastically scaling Kafka engine, 120+ connectors, serverless Apache Flink®, enterprise-grade security controls, and a robust governance suite.

With our [Qdrant-Kafka Sink Connector](https://github.com/qdrant/qdrant-kafka), Qdrant is part of the [Connect with Confluent](https://www.confluent.io/partners/connect/) technology partner program. It brings fully managed data streams directly to organizations from Confluent Cloud, making it easier for organizations to stream any data to Qdrant with a fully managed Apache Kafka service.

## Usage

### Pre-requisites

- A Confluent Cloud account. You can begin with a [free trial](https://www.confluent.io/confluent-cloud/tryfree/?utm_campaign=tm.pmm_cd.cwc_partner_qdrant_tryfree&utm_source=qdrant&utm_medium=partnerref) with credits for the first 30 days.
- Qdrant instance to connect to. You can get a free cloud instance at [cloud.qdrant.io](https://cloud.qdrant.io/).

### Installation

1) Download the latest connector zip file from [Confluent Hub](https://www.confluent.io/hub/qdrant/qdrant-kafka).

2) Configure an environment and cluster on Confluent and create a topic to produce messages for.

3) Navigate to the `Connectors` section of the Confluent cluster and click `Add Plugin`. Upload the zip file with the following info.

![Qdrant Connector Install](/documentation/frameworks/confluent/install.png)

4) Once installed, navigate to the connector and set the following configuration values.

![Qdrant Connector Config](/documentation/frameworks/confluent/config.png)

Replace the placeholder values with your credentials.

5) Add the Qdrant instance host to the allowed networking endpoints.

![Qdrant Connector Endpoint](/documentation/frameworks/confluent/endpoint.png)

7) Start the connector.

## Producing Messages

You can now produce messages for the configured topic, and they'll be written into the configured Qdrant instance.

![Qdrant Connector Message](/documentation/frameworks/confluent/message.png)

## Message Formats

The connector supports messages in the following formats.

_Click each to expand._

<details>
  <summary><b>Unnamed/Default vector</b></summary>

Reference: [Creating a collection with a default vector](https://qdrant.tech/documentation/concepts/collections/#create-a-collection).

```json
{
    "collection_name": "{collection_name}",
    "id": 1,
    "vector": [
        0.1,
        0.2,
        0.3,
        0.4,
        0.5,
        0.6,
        0.7,
        0.8
    ],
    "payload": {
        "name": "kafka",
        "description": "Kafka is a distributed streaming platform",
        "url": "https://kafka.apache.org/"
    }
}
```

</details>

<details>
  <summary><b>Named multiple vectors</b></summary>

Reference: [Creating a collection with multiple vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-multiple-vectors).

```json
{
    "collection_name": "{collection_name}",
    "id": 1,
    "vector": {
        "some-dense": [
            0.1,
            0.2,
            0.3,
            0.4,
            0.5,
            0.6,
            0.7,
            0.8
        ],
        "some-other-dense": [
            0.1,
            0.2,
            0.3,
            0.4,
            0.5,
            0.6,
            0.7,
            0.8
        ]
    },
    "payload": {
        "name": "kafka",
        "description": "Kafka is a distributed streaming platform",
        "url": "https://kafka.apache.org/"
    }
}
```

</details>

<details>
  <summary><b>Sparse vectors</b></summary>

Reference: [Creating a collection with sparse vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-sparse-vectors).

```json
{
    "collection_name": "{collection_name}",
    "id": 1,
    "vector": {
        "some-sparse": {
            "indices": [
                0,
                1,
                2,
                3,
                4,
                5,
                6,
                7,
                8,
                9
            ],
            "values": [
                0.1,
                0.2,
                0.3,
                0.4,
                0.5,
                0.6,
                0.7,
                0.8,
                0.9,
                1.0
            ]
        }
    },
    "payload": {
        "name": "kafka",
        "description": "Kafka is a distributed streaming platform",
        "url": "https://kafka.apache.org/"
    }
}
```

</details>

<details>
  <summary><b>Multi-vectors</b></summary>

Reference:

- [Multi-vectors](https://qdrant.tech/documentation/concepts/vectors/#multivectors)

```json
{
    "collection_name": "{collection_name}",
    "id": 1,
    "vector": {
        "some-multi": [
            [
                0.1,
                0.2,
                0.3,
                0.4,
                0.5,
                0.6,
                0.7,
                0.8,
                0.9,
                1.0
            ],
            [
                1.0,
                0.9,
                0.8,
                0.5,
                0.4,
                0.8,
                0.6,
                0.4,
                0.2,
                0.1
            ]
        ]
    },
    "payload": {
        "name": "kafka",
        "description": "Kafka is a distributed streaming platform",
        "url": "https://kafka.apache.org/"
    }
}
```

</details>

<details>
  <summary><b>Combination of named dense and sparse vectors</b></summary>

Reference:

- [Creating a collection with multiple vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-multiple-vectors).

- [Creating a collection with sparse vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-sparse-vectors).

```json
{
    "collection_name": "{collection_name}",
    "id": "a10435b5-2a58-427a-a3a0-a5d845b147b7",
    "vector": {
        "some-other-dense": [
            0.1,
            0.2,
            0.3,
            0.4,
            0.5,
            0.6,
            0.7,
            0.8
        ],
        "some-sparse": {
            "indices": [
                0,
                1,
                2,
                3,
                4,
                5,
                6,
                7,
                8,
                9
            ],
            "values": [
                0.1,
                0.2,
                0.3,
                0.4,
                0.5,
                0.6,
                0.7,
                0.8,
                0.9,
                1.0
            ]
        }
    },
    "payload": {
        "name": "kafka",
        "description": "Kafka is a distributed streaming platform",
        "url": "https://kafka.apache.org/"
    }
}
```

</details>

## Further Reading

- [Kafka Connect Docs](https://docs.confluent.io/platform/current/connect/index.html)
- [Confluent Connectors Docs](https://docs.confluent.io/cloud/current/connectors/bring-your-connector/custom-connector-qs.html)