You can install Docker Engine on Windows, MacOS or Linux-based operating systems. After you install Docker Engine, you can run Redis Enterprise Software (RS) as Docker containers.

Note: Windows and MacOS are currently only supported for development and testing environments.

To get started with a single Redis Enterprise Software container:

  • Step 1: Install Docker Engine for your operating system
  • Step 2: Run the RS Docker container
  • Step 3: Setup a cluster
  • Step 4: Create a new database
  • Step 5: Connect to your database

Step 1: Install Docker Engine

Go to the Docker installation page for your operating system for detailed instructions about installing Docker Engine:

Step 2: Run the Container

To pull and start the Redis Enterprise Software Docker container, run this docker run command in the terminal or command-line for your operating system.

Note: On Windows, make sure Docker is configured to run Linux-based containers.

$ docker run -d --cap-add sys_resource --name rp -p 8443:8443 -p 12000:12000 redislabs/redis

The Docker container with RS runs on your localhost with port 8443 open for HTTPS connections and with port 12000 open for redis client connections.

Step 3: Setup a Cluster

  1. In the web browser on the host machine, go to https://localhost:8443 to see the Redis Enterprise Software web console.


    • Depending on your browser, you may see a certificate error. You can safely continue to the web console.
    • If you see an error from nginx, try again after a few minutes.
  2. Click Setup to start the node configuration steps.

    Redis Enterprise Software Setup

  3. In the Node Configuration settings, enter a cluster FQDN such as cluster.local. Then click Next button.

    Redis Enterprise Software node configuration

  4. Enter your license key, if you have one. If not, click the Next button to use the trial version.

  5. Enter an email and password for the admin account for the web console.

    Redis Enterprise Software admin credentials

Step 4: Create a Database

  1. Select "redis database" and the "single region" deployment, and click Next.

    Redis Enterprise Software create database

  2. Enter a database name such as database1 and click Activate to create your database.

    Redis Enterprise Software configure new database

Note: If you cannot activate the database because of a memory limitation, make sure that Docker has enough memory allocated in the Advanced section of Docker Settings.

You now have a Redis database!

Step 5: Connect to your Database

After you create the Redis database, you are ready to store data in your database. You can test connectivity to your database with:

  • redis-cli - the built-in command-line tool
  • A Hello World application using Python

Connecting Using redis-cli

redis-cli is a simple command-line tool to interact with Redis database.

Use "docker exec" to switch your context into the Redis Enterprise Software container

$ docker exec -it rp bash

Run redis-cli, located in the /opt/redislabs/bin directory, to connect to port 12000 and store and retrieve a key in database1

$ sudo /opt/redislabs/bin/redis-cli -p 12000> set key1 123
OK> get key1

Connecting Using Hello World Application in Python

A simple python application running on the host machine, not the container, can also connect to database1.

Note: The following section assumes you already have Python and redis-py (python library for connecting to Redis) configured on the host machine running the container. You can find the instructions to configure redis-py on the github page for redis-py.

  1. Create a new file called with this contents:

    import redis
    r = redis.StrictRedis(host='localhost', port=12000, db=0)
    print ("set key1 123")
    print (r.set('key1', '123'))
    print ("get key1")
  2. Run the application to store and retrieve a key:


If the connection is successful, the output of the application looks like this:

set key1 123
get key1

Next steps

Now you have a Redis Enterprise cluster ready to go. You can connect to it with a redis client to start loading it with data or you can use the memtier_benchmark Quick Start to check the cluster performance.