page_title: Managing Data in Containers page_description: How to manage data inside your Docker containers. page_keywords: Examples, Usage, volume, docker, documentation, user guide, data, volumes # Managing Data in Containers So far we've been introduced to some [basic Docker concepts](/userguide/usingdocker/), seen how to work with [Docker images](/userguide/dockerimages/) as well as learned about [networking and links between containers](/userguide/dockerlinks/). In this section we're going to discuss how you can manage data inside and between your Docker containers. We're going to look at the two primary ways you can manage data in Docker. * Data volumes, and * Data volume containers. ## Data volumes A *data volume* is a specially-designated directory within one or more containers that bypasses the [*Union File System*](/terms/layer/#ufs-def) to provide several useful features for persistent or shared data: - Data volumes can be shared and reused between containers - Changes to a data volume are made directly - Changes to a data volume will not be included when you update an image - Volumes persist until no containers use them ### Adding a data volume You can add a data volume to a container using the `-v` flag with the `docker run` command. You can use the `-v` multiple times in a single `docker run` to mount multiple data volumes. Let's mount a single volume now in our web application container. $ sudo docker run -d -P --name web -v /webapp training/webapp python app.py This will create a new volume inside a container at `/webapp`. > **Note:** > You can also use the `VOLUME` instruction in a `Dockerfile` to add one or > more new volumes to any container created from that image. ### Mount a Host Directory as a Data Volume In addition to creating a volume using the `-v` flag you can also mount a directory from your own host into a container. $ sudo docker run -d -P --name web -v /src/webapp:/opt/webapp training/webapp python app.py This will mount the local directory, `/src/webapp`, into the container as the `/opt/webapp` directory. This is very useful for testing, for example we can mount our source code inside the container and see our application at work as we change the source code. The directory on the host must be specified as an absolute path and if the directory doesn't exist Docker will automatically create it for you. > **Note:** > This is not available from a `Dockerfile` due to the portability > and sharing purpose of it. As the host directory is, by its nature, > host-dependent, a host directory specified in a `Dockerfile` probably > wouldn't work on all hosts. Docker defaults to a read-write volume but we can also mount a directory read-only. $ sudo docker run -d -P --name web -v /src/webapp:/opt/webapp:ro training/webapp python app.py Here we've mounted the same `/src/webapp` directory but we've added the `ro` option to specify that the mount should be read-only. ### Mount a Host File as a Data Volume The `-v` flag can also be used to mount a single file - instead of *just* directories - from the host machine. $ sudo docker run --rm -it -v ~/.bash_history:/.bash_history ubuntu /bin/bash This will drop you into a bash shell in a new container, you will have your bash history from the host and when you exit the container, the host will have the history of the commands typed while in the container. > **Note:** > Many tools used to edit files including `vi` and `sed --in-place` may result > in an inode change. Since Docker v1.1.0, this will produce an error such as > "*sed: cannot rename ./sedKdJ9Dy: Device or resource busy*". In the case where > you want to edit the mounted file, it is often easiest to instead mount the > parent directory. ## Creating and mounting a Data Volume Container If you have some persistent data that you want to share between containers, or want to use from non-persistent containers, it's best to create a named Data Volume Container, and then to mount the data from it. Let's create a new named container with a volume to share. $ sudo docker run -d -v /dbdata --name dbdata training/postgres echo Data-only container for postgres You can then use the `--volumes-from` flag to mount the `/dbdata` volume in another container. $ sudo docker run -d --volumes-from dbdata --name db1 training/postgres And another: $ sudo docker run -d --volumes-from dbdata --name db2 training/postgres You can use multiple `--volumes-from` parameters to bring together multiple data volumes from multiple containers. You can also extend the chain by mounting the volume that came from the `dbdata` container in yet another container via the `db1` or `db2` containers. $ sudo docker run -d --name db3 --volumes-from db1 training/postgres If you remove containers that mount volumes, including the initial `dbdata` container, or the subsequent containers `db1` and `db2`, the volumes will not be deleted. To delete the volume from disk, you must explicitly call `docker rm -v` against the last container with a reference to the volume. This allows you to upgrade, or effectively migrate data volumes between containers. ## Backup, restore, or migrate data volumes Another useful function we can perform with volumes is use them for backups, restores or migrations. We do this by using the `--volumes-from` flag to create a new container that mounts that volume, like so: $ sudo docker run --volumes-from dbdata -v $(pwd):/backup ubuntu tar cvf /backup/backup.tar /dbdata Here we've launched a new container and mounted the volume from the `dbdata` container. We've then mounted a local host directory as `/backup`. Finally, we've passed a command that uses `tar` to backup the contents of the `dbdata` volume to a `backup.tar` file inside our `/backup` directory. When the command completes and the container stops we'll be left with a backup of our `dbdata` volume. You could then restore it to the same container, or another that you've made elsewhere. Create a new container. $ sudo docker run -v /dbdata --name dbdata2 ubuntu /bin/bash Then un-tar the backup file in the new container's data volume. $ sudo docker run --volumes-from dbdata2 -v $(pwd):/backup busybox tar xvf /backup/backup.tar You can use the techniques above to automate backup, migration and restore testing using your preferred tools. # Next steps Now we've learned a bit more about how to use Docker we're going to see how to combine Docker with the services available on [Docker Hub](https://hub.docker.com) including Automated Builds and private repositories. Go to [Working with Docker Hub](/userguide/dockerrepos).