Kafka and Redis integration

Save yourself the work of writing custom integrations for Kafka and Redis and use n8n instead. Build adaptable and scalable Development, and Data & Storage workflows that work with your technology stack. All within a building experience you will love.

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How to connect Kafka and Redis

Step 1: Create a new workflow
Step 2: Add and configure nodes
Step 3: Connect
Step 4: Customize and extend your integration
Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Kafka and Redis integration: Create a new workflow and add the first step

Step 2: Add and configure Kafka and Redis nodes

You can find Kafka and Redis in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Kafka and Redis nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Kafka and Redis integration: Add and configure Kafka and Redis nodes

Step 3: Connect Kafka and Redis

A connection establishes a link between Kafka and Redis (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Kafka and Redis integration: Connect Kafka and Redis

Step 4: Customize and extend your Kafka and Redis integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Kafka and Redis with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Kafka and Redis integration: Customize and extend your Kafka and Redis integration

Step 5: Test and activate your Kafka and Redis workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Kafka to Redis or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Kafka and Redis integration: Test and activate your Kafka and Redis workflow

Build your own Kafka and Redis integration

Create custom Kafka and Redis workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Redis supported actions

Delete

Delete a key from Redis

Get

Get the value of a key from Redis

Increment

Atomically increments a key by 1. Creates the key if it does not exist.

Info

Returns generic information about the Redis instance

Keys

Returns all the keys matching a pattern

Pop

Pop data from a redis list

Publish

Publish message to redis channel

Push

Push data to a redis list

Set

Set the value of a key in redis

Kafka and Redis integration details

Kafka is an open-source platform for distributed event streaming that may be used for mission-critical applications, high-performance data pipelines, streaming analytics, and data integration. The largest companies in the world, in different sectors, are using Kafka.

Kafka node docs + examples

Kafka credential docs

See Kafka integrations

Related categories

Development

Redis is an open-source, advanced key-value store. It is often referred to as a data structure server. Its high performance makes it a favorite fast data store, cache, and even lightweight message broker.

Redis node docs + examples

Redis credential docs

See Redis integrations

Related categories

Development

Data & Storage

Other integrations with Kafka