Redis Kafka Sink Connector for Confluent Cloud

The fully-managed Redis Kafka Sink connector for Confluent Cloud maps and writes records from Apache Kafka® topics directly to a Redis database. The connector supports AVRO, BYTES, JSON, JSON Schema, PROTOBUF, and STRING data formats from Apache Kafka® topics. The connector reads records from a Kafka topic and writes them to Redis., making the data available for querying, enrichment, and analytics.

Features

The fully-managed Redis Kafka Sink connector provides the following features:

  • At least once delivery: The connector guarantees that records are written at least once to Redis.
  • Database authentication: The connector supports password-based authentication.
  • Compatibility: The connector supports Redis-compatible databases, including AWS Valkey and AWS MemoryDB.
  • Redis data structure: The connector supports STREAM, LIST, SET, ZSET, STRING, HASH, TIMESERIES, JSON Redis data-structure types as targets.
  • Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.
  • Input data formats: The connector accepts AVRO, BYTES, JSON, JSON_SR (JSON Schema), PROTOBUF, or STRING input data formats for record keys and values. Schema Registry must be enabled to use a Schema Registry-based format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF). For more information, see Schema Registry Enabled Environments.
  • Time to live (TTL) support: The connector supports allows you to set a TTL for Redis keys to automatically expire data after a specified duration.
  • Multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.

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

Limitations

Be sure to review the following information.

Quick Start

Use this quick start to get up and running with the Confluent Cloud Redis Kafka Sink connector. The quick start provides the basics of selecting the connector and configuring it to consume data from Kafka and persist the data to a Redis Kafka database.

Prerequisites
  • 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 Redis Kafka Sink connector card.

Redis Kafka Sink Connector Card

Step 4: Enter the connector details

Note

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

At the Add Redis Kafka Sink Connector screen, complete the following:

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.

Step 5: Check Redis database

After the connector is running, verify that messages are being added to your Redis database.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.

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 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.

{
    "connector.class": "RedisKafkaSink",
    "name": "RedisKafkaSinkConnector_0",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "<my-kafka-api-key",
    "kafka.api.secret": "<my-kafka-api-secret>",
    "redis.host": "test-18211.c90.us-east-1.ec2.redis-cloud.com",
    "redis.port": "18211",
    "redis.database": "0",
    "redis.tls": "false",
    "redis.timeout": "60",
    "redis.pool": "8",
    "redis.server.mode": "Standalone",
    "topics": "keys_source",
    "input.data.format" : "JSON",
    "input.key.format" : "STRING",
    "redis.charset": "UTF-8",
    "redis.type": "STREAM",
    "redis.multiexec": "false",
    "redis.separator": ":",
    "redis.wait.replicas": "0",
    "redis.key.ttl": "-1",
    "tasks.max": "1",
    "auto.restart.on.user.error": "true"
}

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

  • "input.data.format": Sets the input Kafka record value format (data coming from the Kafka topic). Valid entires are AVRO, BYTES, JSON, JSON_SR (JSON Schema), PROTOBUF, or STRING. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF).

  • "input.key.format": Sets the input record key format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR (JSON Schema), PROTOBUF, or STRING. You must have Confluent Cloud Schema Registry configured if using a schema-based message format.

  • "redis.host": The IP address or hostname of the Redis database server.

  • "redis.port": The port number used to connect to Redis database server.

  • "redis.tls": Specify whether to use Transport Layer Security (TLS) to connect to the Redis database. Defaults to false.

  • "tasks.max": Enter the number of tasks for the connector. For more information, see Confluent Cloud connector limitations.

Note

(Optional) To enable CSFLE for data encryption, specify the following properties:

  • csfle.enabled: Flag to indicate whether the connector honors CSFLE 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.

Warning

Security Risk: Dead Letter Queue (DLQ) with CSFLE

When using CSFLE with connectors that route failed messages to a Dead Letter Queue (DLQ), be aware that data sent to the DLQ is written in plaintext (unencrypted). 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 in the current version. If you need error handling for CSFLE-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 setup, see Manage CSFLE for connectors.

Single Message Transforms: For more information about adding SMTs using the CLI, see Single Message Transforms (SMT) documentation.

See Configuration Properties for all property values and definitions.

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 RedisKafkaSink.json

Example output:

Created connector confluent-RedisKafkaSink lcc-ix4dl

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-ix4dl   | confluent-RedisKafkaSink | RUNNING | sink

Step 6: Check Redis Kafka

After the connector is running, verify that records are populating your Redis Kafka database.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.

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

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

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.

  • Type: string
  • Default: KAFKA_API_KEY
  • Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
  • 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

Redis connection

redis.host

The hostname of Redis server to connect to.

  • Type: string
  • Importance: high
redis.port

The port number of Redis server to connect to.

  • Type: string
  • Importance: high
redis.database

The database index to write to.

  • Type: int
  • Default: 0
  • Importance: medium
redis.username

The username of the Redis user connecting to the Redis database server.

  • Type: string
  • Importance: medium
redis.password

The password of the Redis user connecting to the Redis database server.

  • Type: password
  • Importance: medium

Redis security

redis.tls

Establish a secure TLS connection to Redis.

  • Type: boolean
  • Default: false
  • Importance: medium
redis.cacert

X.509 CA certificate file to verify with. Use this with or without client certificates.

  • Type: password
  • Importance: medium

Redis client certificate auth

redis.key.file

Private key file (PEM format) to authenticate with. Use this file along with the certificate file for client certificate authentication.

  • Type: password
  • Importance: medium
redis.key.cert

X.509 certificate chain file (PEM format) to authenticate with. Use this file along with the private key file for client certificate authentication.

  • Type: password
  • Importance: medium
redis.key.password

Password of the private key file. Leave empty if key file is not password-protected.

  • Type: password
  • Importance: medium

Redis data structure

redis.type

Destination Redis data structure. Valid entries are STREAM, LIST, SET, ZSET, STRING, HASH, TIMESERIES, or JSON. Note that multi/exec transactions only work with STREAM, LIST, SET, or ZSET data types.

  • Type: string
  • Default: STREAM
  • Importance: high

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.

  • Type: string
  • Default: JSON
  • Importance: high
input.key.format

Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF

  • Type: string
  • Default: BYTES
  • Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING
  • Importance: high

Redis configuration

redis.keyspace

A format string for destination key space, which may contain ${topic} as a placeholder for the originating topic name. For example, kafka_${topic} for the topic orders will map to the Redis key space kafka_orders.

  • Type: string
  • Default: ${topic}
  • Importance: medium
redis.separator

Separator for non-collection destination keys.

  • Type: string
  • Default: :
  • Importance: medium
redis.key.ttl

Time to live in seconds for the key to automatically expire data after a specified duration. If not set (default -1), the record will not expire.

  • Type: long
  • Default: -1
  • Valid Values: [-1,…,2147483647]
  • Importance: medium
redis.multiexec

Whether to execute Redis commands in multi/exec transactions. Only works with STREAM, LIST, SET, or ZSET data types.

  • Type: boolean
  • Default: false
  • Importance: medium
redis.wait.replicas

Number of replicas to wait for. Use 0 to disable waiting for replicas.

  • Type: int
  • Default: 0
  • Valid Values: [0,…,100]
  • Importance: medium
redis.charset

Character set to encode Redis key and value strings. Must be a valid charset name.

  • Type: string
  • Default: UTF-8
  • Importance: high
redis.wait.timeout

Timeout in milliseconds for WAIT command.

  • Type: long
  • Default: 1000
  • Valid Values: [1,…,60000]
  • Importance: medium
redis.timeout

Redis command timeout in seconds.

  • Type: long
  • Default: 60
  • Valid Values: [1,…,3600]
  • Importance: medium
redis.pool

Maximum number of connections in the pool in the range of 1 to 100.

  • Type: int
  • Default: 8
  • Valid Values: [1,…,100]
  • Importance: medium
redis.server.mode

Whether redis server is running on one or multiple nodes.

  • Type: string
  • Default: Standalone
  • 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

  • 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
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.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.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.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

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.

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