Install Memgraph with Docker
Docker is a service that uses OS-level virtualization to deliver software in packages that are called containers.
Memgraph uses Docker because it is:
- Flexible
- Lightweight
- Portable - you can build locally or deploy to the cloud
- Runs on all platforms - Windows, Linux and macOS
- Deploys in Kubernetes
Memgraph bundles the database along with various analytical tools into distinct Docker images.
Available Docker images
All Memgraph Docker images are available at Memgraph’s Docker Hub. There you will find the exact Docker image tags you can use to install Memgraph with.
The main repositories that contain memgraph are:
memgraph/memgraph-mage- includes Memgraph database, command-line interfacemgconsoleandMAGEgraph algorithms library.memgraph/memgraph- includes Memgraph database and command-line interfacemgconsole.
There are also two additional standalone images that do not include the Memgraph:
memgraph/lab- includes a web interface Memgraph Lab that helps you explore the data stored in Memgraph.memgraph/mgconsole- includes a command-line interfacemgconsolethat allows you to interact with Memgraph from the command line.
To use Memgraph, run
memgraph/memgraph-mage,
memgraph/memgraph-mage +
cuGraph
or
memgraph/memgraph
image. To query Memgraph, use the CLI mgconsole. If you prefer a visual user
interface to query Memgraph, run
memgraph/lab
image or download Desktop
application from Memgraph Download
hub and connect to the running Memgraph instance.
Memgraph and Memgraph Lab can be run as a multi-container application - Memgraph Platform. To do that, run the above images as services with Docker Compose.
Run Memgraph MAGE Docker image
Install and run the memgraph-mage image using the following command:
docker run -p 7687:7687 -p 7444:7444 --name memgraph memgraph/memgraph-mageYou can connect to the Memgraph instance using the command-line interface mgconsole by running the following command in a new terminal:
docker exec -it memgraph mgconsoleYou can also connect to Memgraph instance using the Memgraph Lab, available for download from Memgraph’s Download Hub, or using the Memgraph Lab Docker image.
To start using Memgraph in your application, use one of the client libraries and follow their getting started guide.
Run Memgraph MAGE Docker image + cuGraph
These instructions are listed here as a reference for legacy installations.
We currently do not produce MAGE images with cuGraph (since version 1.3). If this is something you require, please raise an issue
Check prerequisites
To be able to run cuGraph analytics, make sure you have compatible infrastructure first. The exact system requirements are available at the NVIDIA RAPIDS site, and include an NVIDIA Pascal (or better) GPU and up-to-date CUDA & NVIDIA drivers.
You will also need to install:
- Official NVIDIA driver for your operating system.
- To run on NVIDIA-powered GPUs, RAPIDS requires Docker CE v19.03+ and nvidia-container-toolkit.
- Legacy Docker CE v17-18 users requie the nvidia-docker2 package.
Install and run Memgraph
Install and run Memgraph using the following command:
docker run --rm --gpus all -p 7687:7687 -p 7444:7444 memgraph/memgraph-mage:1.3-cugraph-22.02-cuda-11.5Check the latest versions of cuGraph Docker images at Memgraph’s Docker
Hub, by searching the
memgraph/memgraph-mage repository with the cugraph keyword.
You can connect to the Memgraph instance using the command-line interface mgconsole by running the following command in a new terminal:
docker exec -it memgraph mgconsoleYou can also connect to Memgraph instance using the Memgraph Lab, available for download from Memgraph’s Download Hub.
To start using Memgraph in your application, use one of the client libraries and follow their getting started guide.
Run Memgraph Docker image
Install and run the memgraph image using the following command:
docker run -p 7687:7687 -p 7444:7444 --name memgraph memgraph/memgraphYou can connect to the Memgraph instance using the command-line interface mgconsole by running the following command in a new terminal:
docker exec -it memgraph mgconsoleYou can also connect to Memgraph instance using the Memgraph Lab, available for download from Memgraph’s Download Hub.
To start using Memgraph in your application, use one of the client libraries and follow their getting started guide.
Load and run Memgraph Docker image from Memgraph download hub
If you’ve downloaded the Memgraph Docker image directly from the Memgraph
download hub, you’ll receive a file named
similar to memgraph-3.1.1-docker.tar.gz (the exact file name varies based on
the version you’ve downloaded).
To load this image into Docker, do the following:
Load the image into Docker
Use the docker load command to load the
image into Docker:
docker load -i memgraph-3.1.1-docker.tar.gzRun the Memgraph image
After loading the image, you can run it using the docker run command. Here’s
an example command to start the Memgraph Docker container:
docker run -p 7687:7687 -p 7444:7444 --name memgraph memgraph/memgraph:2.18.0The :2.18.0 part in the docker run command refers to the tag of the Docker
image. It is important to specify the correct tag corresponding to the version
of Memgraph you have downloaded and loaded.
To find the available tags for your images, you can use the docker images
command. This command lists all Docker images on your system, including their
tags.
Docker allows multiple versions of the same image to coexist, each tagged with a
different version number. If no tag is specified, Docker will default to using
the :latest tag.
Run Memgraph Lab image
Install and run the lab image using the following command:
docker run -d -p 3000:3000 --name lab memgraph/labOnce the container is up you can access Memgraph Lab on localhost:3000.
Issues when connecting to Memgraph Lab to Memgraph
Issues when linking Memgraph Lab with Memgraph can come from the chosen
deployment method and the operating system deployed. The handling of the
QUICK_CONNECT_MG_HOST environment variable differs based on the operating
system:
-
Mac or Windows: The
host.docker.internalhostname allows Docker containers to connect to the host machine. Set this as the value forQUICK_CONNECT_MG_HOSTwhen running Lab on Mac or Windows to enable connection to Memgraph running on the host:docker run -d -p 3000:3000 -e QUICK_CONNECT_MG_HOST=host.docker.internal --name lab memgraph/lab -
Linux: There’s no need to set
QUICK_CONNECT_MG_HOSTas it defaults tolocalhost, assuming Memgraph is running locally on the host machine.
You can also use the QUICK_CONNECT_MG_PORT environment variable to specify the
quick connect port number, e.g. - e QUICK_CONNECT_MG_PORT=7688.
Configuration options
To learn about all the configuration options, check out the configuration settings.
When using Docker, you can specify the configuration options in the docker run
command:
docker run memgraph/memgraph --bolt-port=7687 --log-level=TRACEInstall Memgraph Platform image up to version 2.14
These instructions are listed here as a reference for legacy installations.
Starting with version 2.15, Memgraph Platform transitions to a multi-container application. This upgrade moves from a single Docker image to separate containers for Memgraph+MAGE and Memgraph Lab, utilizing Docker Compose for deployment and management.
For detailed setup instructions and best practices, please refer to the Docker Compose documentation for Memgraph Platform.
Please note that the Memgraph Platform Docker image is no longer being updated.
Install Docker Desktop
Install Docker Desktop by following the instructions available on their site.
Install and run Memgraph
Open a terminal and use the following command:
docker run -p 7687:7687 -p 7444:7444 -p 3000:3000 --name memgraph memgraph/memgraph-platformAfter downloading the image, Memgraph will install and if the installation was successful, you should see a message similar to the following:
C:\Users\Vlasta>docker run -p 7687:7687 -p 7444:7444 -p 3000:3000 --name memgraph memgraph/memgraph-platform
2023-08-29 09:02:59,833 INFO Included extra file "/etc/supervisor/programs/lab.conf" during parsing
2023-08-29 09:02:59,834 INFO Included extra file "/etc/supervisor/programs/memgraph.conf" during parsing
2023-08-29 09:02:59,834 INFO Set uid to user 0 succeeded
2023-08-29 09:02:59,842 INFO supervisord started with pid 1
2023-08-29 09:03:00,845 INFO spawned: 'memgraph' with pid 7
2023-08-29 09:03:00,848 INFO spawned: 'lab' with pid 8
You are running Memgraph v2.10.1
To get started with Memgraph, visit https://memgr.ph/start
[2023-08-29 09:03:01.034] [memgraph_log] [warning] Invalid license key string. To use Enterprise features please set it to a valid string using the following query:
SET DATABASE SETTING "enterprise.license" TO "your-license-key"
[2023-08-29 09:03:01.333] [memgraph_log] [warning] No snapshot or WAL file found. For more details, visit https://memgr.ph/durability.
[2023-08-29 09:03:01.333] [memgraph_log] [warning] Replication configuration will NOT be stored. When the server restarts, replication state will be forgotten.
2023-08-29 09:03:02,334 INFO success: memgraph entered RUNNING state, process has stayed up for > than 1 seconds (startsecs)
2023-08-29 09:03:02,335 INFO success: lab entered RUNNING state, process has stayed up for > than 1 seconds (startsecs)
[2023-08-29 09:03:02.803] INFO: [lab] Lab is running at http://localhost:3000 in platform mode
DGL backend not selected or invalid. Assuming PyTorch for now.
<frozen importlib._bootstrap>:228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
[2023-08-29 09:03:09.257] [memgraph_log] [error] Unable to load module "/usr/lib/memgraph/query_modules/libmgclient.so"; /usr/lib/memgraph/query_modules/libmgclient.so: undefined symbol: mgp_init_module. For more details, visit https://memgr.ph/modules.
[2023-08-29 09:03:09.542] [memgraph_log] [error] Unable to load module "/usr/lib/memgraph/query_modules/example_cpp.so"; /usr/lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.29' not found (required by /usr/lib/memgraph/query_modules/example_cpp.so). For more details, visit https://memgr.ph/modules.
[2023-08-29 09:03:09.542] [memgraph_log] [warning] Using non-secure Bolt connection (without SSL). For more details, visit https://memgr.ph/ssl.Memgraph will start listing the logs, and don’t worry about the inital errors and warnings as at this point, they are of informative nature.
Connect to the instance
You can connect to the Memgraph instance using the command-line interface mgconsole by running the following command in a new terminal:
docker run -it memgraph/mgconsole:latestWhen the mgconsole starts, you can query the database:
docker run -it memgraph/mgconsole:latest
mgconsole 1.4
Connected to 'memgraph://127.0.0.1:7687'
Type :help for shell usage
Quit the shell by typing Ctrl-D(eof) or :quit
memgraph>You can also connect to Memgraph using the Memgraph Lab web
application available within the
memgraph-platform Docker image by visiting localhost:3000.

To start using Memgraph in your application, use one of the client libraries and follow their getting started guide.
Running individual tools from Memgraph Platform image
You can run only the Memgraph database instance from the Memgraph Platform image using the following command:
docker run -p 7687:7687 memgraph/memgraph-platform -c /etc/supervisor/supervisord-memgraph-only.confYou can run only mgconsole from the Memgraph Platform image using the following command in Linux:
docker run -it --entrypoint=mgconsole memgraph/memgraph-platformYou can run only mgconsole application from the Memgraph Platform image using the following command in Windows and macOS:
docker run -it --entrypoint=mgconsole memgraph/memgraph-platform --host host.docker.internalYou can also consider using a standalone mgconsole image as described in the CLI section.
You can run only the Memgraph Lab web application from the Memgraph Platform image using the following command:
docker run -p 3000:3000 memgraph/memgraph-platform -c /etc/supervisor/supervisord-lab-only.confStop and start the instance
You can stop the instance with docker stop memgraph.
You can restart the instance with docker start memgraph
Troubleshooting
Issues with loading Memgraph
docker load -i memgraph.tar.gzError during connect:
This error may indicate that the docker daemon is not running.
Run the Docker Desktop application and wait for it to load fully.
Error response from daemon:
open \\.\pipe\docker_engine_linux: The system cannot find the file specified.
Reload the Docker Desktop application and wait for it to load fully.
Unsupported OS Linux
You need to download the Windows Subsystem for Linux, and enable experimental features in Docker Desktop, under Settings -> Docker Engine, change experimental to true.
Issues when connecting to Memgraph Platform up to version 2.14
docker run memgraph/memgraph-platformWhile this command will start a Memgraph instance, not publishing the port will
cause problems when trying to connect to the database via Memgraph Lab or
mgconsole. To avoid this, you should publish the
container’s port to the host using the -p flag and by specifying the port:
docker run -p 7687:7687 -p 7444:7444 -p 3000:3000 memgraph/memgraph-platformIssues with connecting mgconsole to the database
docker run -it --entrypoint=mgconsole memgraph/memgraph-platform --host HOSTAlthough unlikely, sometimes there are issues with connecting mgconsole to
the Docker Container’s IP address because it is running on a custom IP rather
than localhost. This problem is most often accompanied with the following
error:
Connection failure: Couldn't connect to 127.0.0.1:7687!To fix this issue, just replace HOST from the first command with
host.docker.internal. To find out more about networking in Docker, take a look
at Networking features in Docker Desktop for
Windows guide or
Mac guide .
Issues with the IP address
Although unlikely, some users might experience minor difficulties after the
Docker installation. Instead of running on localhost, a Docker container for
Memgraph may be running on a custom IP address. Fortunately, that IP address can
be found as follows:
1. Determine the ID of the Memgraph Container by issuing the
command docker ps. The user should get an output similar to the following:
CONTAINER ID IMAGE COMMAND CREATED
9397623cd87e memgraph "/usr/lib/memgraph/m…" 2 seconds agoAt this point, it is important to remember the container ID of the Memgraph
Image. In our case, that is 9397623cd87e.
2. Use the this ID to retrieve the IP address of the Container:
docker inspect -f '{{range.NetworkSettings.Networks}}{{.IPAddress}}{{end}}' 9397623cd87eThe command above will yield the IP address that should be used when connecting
to Memgraph via Memgraph Lab or mgconsole. Just replace
HOST from the following command with the appropriate IP address:
docker run -it --entrypoint=mgconsole memgraph/memgraph-platform --host HOST