Persisting data with Docker volumes

Docker containers are ephemeral. When a container is stopped, any data written to it is lost. Therefore, if you want to persist data when using Neo4j in Docker, you must mount storage to the container. Storages also allow you to get data in and out of the container.

Storage can be mounted to a container in two ways:

  • A folder on the host file system.

  • A Docker volume — a named storage location that is managed by Docker.

For instructions on how to mount storage to a Docker container, refer to the official Docker documentation Bind mounts and Volumes.

Neo4j provides several mount points for storage to simplify using Neo4j in Docker. The following sections describe the mount points and how to use them.

Neo4j mount points and permissions

The following table is a complete reference of the mount points recognized by the Neo4j Docker image, and file permissions.

All the listed mount points are optional. Neo4j can run in Docker without any volumes mounted at all. However, mounting storage to /data is considered essential for all but the most basic use cases.

Running containerized Neo4j without a /data mount results in unrecoverable data loss if anything happens to the container.
Table 1. Mount points for the Neo4j container
Mount point Permissions required Description

/data

read, write

The data store for the Neo4j database. See Mounting storage to /data.

/logs

read, write

Output directory for Neo4j logs. See Mounting storage to /logs.

/conf

read[1]

Pass configuration files to Neo4j on startup.
See Modify the default configuration.

/plugins

read[2]

Allows you to install plugins in containerized Neo4j.
See Plugins.

/licenses

read

Provide licenses for Neo4j and any plugins by mounting the license folder.
See Installing Plugin Licenses.

/import

read

Make csv and other importable files available to neo4j-admin import.

/ssl

read

Provide SSL certificates to Neo4j for message encryption.
See SSL encryption in a Neo4j Docker container

/metrics

write

Enterprise Edition Output directory for metrics files. See Metrics.
1. Write permissions are required when using the dump-config feature.
2. Write permissions are required when using the NEO4J_PLUGINS feature to download and store plugins.

Keep in mind that mounted directories are connected to Neo4j by matching internal paths. If you build custom plugins directly into the image or want to bypass the Docker entrypoint automation in custom environments, you can explicitly override or bind the location by defining the server.directories.plugins setting. Note that the configuration directory itself cannot be changed this way; it is driven entirely by the NEO4J_CONF environment variable.

Mounting storage to /data

Neo4j inside Docker stores database files in the /data folder. By mounting storage to /data, any data written to Neo4j will persist after the container is stopped.

Stopping the container and then restarting with the same folder mounted to /data starts a new containerized Neo4j instance with the same data.

If Neo4j could not properly close down, it may have left data in a bad state and is likely to fail on startup. This is the same as if Neo4j is run outside a container and not closed properly.
Example 1. Two ways to mount storage to the /data mount point
Mounting a folder to /data
docker run -it --rm \
   --volume $HOME/neo4j/data:/data \
   neo4j:2026.08.1
Creating a named volume and mounting it to /data
docker volume create neo4jdata (1)
docker run -it --rm \
   --volume neo4jdata:/data \  (2)
   neo4j:2026.08.1
1 Create a Docker volume named neo4jdata.
2 Mount the volume name neo4jdata to /data.

Mounting storage to /logs

Neo4j logging output is written to files in the /logs directory. This directory is mounted as a /logs volume. By mounting storage to /logs, the log files become available outside the container.

For more information about configuring Neo4j, see Configuration.
For more information about the Neo4j log files, see Logging.

File permissions

For security reasons, by default, Neo4j runs as the neo4j user inside the container. This user has user ID 7474. If neo4j needs read or write access to a mounted folder, but does not have it, the folder will be automatically re-owned to 7474.

This is a convenient feature, so you do not have to worry about the finer details of file permissions in Docker and can get started more easily. It does however mean that mounted folders change ownership, and you may find you can no longer read your files without root access.

Docker run with --user flag

The --user flag to docker run forces Docker to run as the provided user. In this situation, if that user does not have the required read or write access to any mounted folders, Neo4j will fail to start.

Glossary

allocator

A component in the cluster that allocates databases to servers according to the topology constraints specified and an allocation strategy.

asynchronous replication

Asynchronous replication is used by secondary copies to poll for new transactions, which means they cannot be guaranteed to have received the most recent transactions. This enables efficient scale-out of read-performance.

Aura instance

A fully-managed DBMS represented by a single instance ID, that is running in the Neo4j Aura cloud.

auto-commit transaction

An automatically committed transaction that contains a single query.

Bolt protocol

Bolt is a protocol used for interaction between Neo4j instances and drivers.

bookmark

A marker the client can request from the cluster to ensure that it is able to read its own writes so that the application’s state is consistent and only databases that have a copy of the bookmark are permitted to respond.

category (Bloom)

A category is based on a node label and is defined in a Perspective as a way of visually distinguishing nodes with the same label(s).

causal consistency

All servers in a cluster agree on the order in which transactions take place. The position of a server on the causal chain can be guaranteed using a bookmark.

cluster

A Neo4j DBMS that spans multiple servers working together to increase fault tolerance and/or read scalability. Databases on a cluster may be configured to replicate across servers in the cluster thus achieving read scalability or high availability.

client application

Software that interacts with a Neo4j server.

commit

A commit is the successful completion of a transaction, which ensures durability of any changes made. For more details, visit Operations Manual → Transaction management.

composite database

Composite databases are the means to access partitioned graph data with a single Cypher query.

constraint

Constraints are sets of data modeling rules that ensure the data is consistent and reliable.

Cypher®

Neo4j’s graph query language.

data model

A data model defines how information is organized in a database. A good data model will make querying and understanding your data easier. In Neo4j, the data models have a graph structure.

database

A database is a container used by the DBMS to manage and store graph data. The physical structure of data is controlled by the database.

database vs graph

Databases are the physical containers of graph data. Graphs are the logical structure of data in Neo4j.

Database Management System

Database Management System, or DBMS, capable of managing multiple databases. A DBMS may run on a single server, or span several servers configured as a cluster.

database schema

The prescribed property existence and datatypes for nodes and relationships.

deallocate

An act of removing a database from a server or a server from a cluster without loss of data or reduced fault tolerance.

degree (of a node)

The number of relationships of a specific node; loops are counted twice.

disaster recovery

A manual intervention to restore availability of a cluster, or databases within a cluster.

driver

A software library that provides access to Neo4j from a particular programming language.

election

In the event that the Raft leader becomes unresponsive, followers automatically trigger an election and vote for a new leader.

entity

A node or a relationship.

expression (Cypher)

A component of a Cypher query which produces values. It may be used in projections, as a predicate, or when setting properties on graph elements.

fabric

Fabric is the architectural design of a unified system that provides a single access point to local or distributed graph data.

fault tolerance

A guarantee that a cluster can maintain a database’s persistence and availability in the event of one or more servers failing.

follower

A primary copy of a database acting as a follower, receives and acknowledges synchronous writes from the leader.

Generative AI (GenAI)

A type of artificial intelligence (AI) system that generates text, images, or other media in response to prompts.

graph

A logical representation of a set of nodes where some pairs are connected by relationships.

index

Data structure that improves read performance of a database.

knowledge graph

A specific type of graph that has an organizing principle so that a user (or a computer system) can reason about the underlying data. The organizing principle provides an additional layer of structure that adds context to support knowledge discovery.

label

Marks a node as a member of a named and indexed subset. A node may be assigned zero or more labels.

leader

A single primary copy of a database is designated as the leader. It receives all write transactions from clients and replicates writes synchronously to followers and asynchronously to secondary copies of the database.

main database

In terms of Neo4j Enterprise Studio, the database(s) containing the user’s data. Can exist in the same Neo4j deployment as the tool asset database.

motif

A description of a specific pattern within a graph.

node

A node represents an entity or discrete object in your graph data model. Nodes can be connected by relationships, hold data in properties, and are classified by labels.

operator

A symbol representing a mathematical or logical operation.

parameter

Named value provided when running a Cypher statement.

path

A sequence of nodes and the relationships connecting them, that does not contain duplicate relationships. Several paths can match a pattern.

pattern

A specific arrangement of nodes and relationships that can be matched in a graph. A pattern follows a motif.

perspective (Bloom)

A Perspective defines a certain business view or domain that can be found in the target Neo4j graph. A single Neo4j graph can be viewed through different Perspectives, each tailored for a different business purpose.

primary

A copy of the database that is able to process write transactions and is eligible to be elected as a leader. It participates in fault tolerant writes as it is part of the majority required to acknowledge and commit write transactions.

primary vs secondary

In a cluster, databases can operate in either primary or secondary mode. Primary databases are able to process write and read transactions, ensuring fault tolerance. Secondary databases are replicated asynchronously from primaries, and their main purpose is to provide read scaling within the cluster.

project (Aura)

An isolated environment in the unified Aura console that contains its own database instances, configurations, and resources. Preceded by tenant in the classic Aura console.

property

Properties are key-value pairs that are used for storing data on nodes and relationships.

query (Cypher)

A statement that retrieves or writes information to a database.

Raft group

A group of servers that are participating in hosting a particular database in primary mode.

Raft group member

A server that is participating in a Raft group. A server can be a member of one or more groups.

Raft log

A shared log between all Raft group members that is guaranteed to be consistently updated and viewed by those members. The log contains both database data and operational state of the Raft group.

Raft protocol

The networking mechanism that enables a database to replicate its data across multiple servers to give high availability for accessing the data and high durability to the data stored.

read scaling

Distributing query load by creating additional database copies hosted in secondary mode (read-only).

relationship

A relationship represents a connection between nodes in your graph data model. Relationships connect a source node to a target node, hold data in properties, and are classified by type.

secondary

An asynchronously replicated copy of the database that provides read scaling within the cluster.

seed

A seed is a database dump or a full backup used to create a database on a cluster. This is sometimes called seeding.

server

A physical machine, a virtual machine, or a container running an instance of Neo4j. Servers can be standalone or part of a cluster.

session

A causally linked sequence of transactions.

session consistency

An alternative name for Neo4j’s causal consistency.

standalone

A single server running Neo4j and not part of a cluster.

synchronous replication

Synchronous replication requires the leader primary to replicate a transaction and block the commit until a quorum of the follower primaries acknowledges that the transaction is successfully replicated. Once the transaction is replicated, the commit is allowed to proceed. This ensures data durability and consistency within the cluster.

system database

A database used by Neo4j to store system information.

tenant (Aura)

An isolated environment in the classic Aura console that contains its own database instances, configurations, and resources. Replaced by project in the unified Aura console.

tool asset database

In terms of Neo4j Enterprise Studio, the database where tools' assets are stored. This can be in the same Neo4j deployment as the main database(s) or in a separate deployment.

topology

A configuration that describes how the copies of a database should be spread across the servers in a cluster, see primary mode and secondary mode.

transaction

A transaction comprises a unit of work performed against a database. It is treated in a coherent and reliable way, independent of other transactions. Transactions comply with the ACID consistency model (atomic, consistent, isolated, and durable).