Deploying a Neo4j cluster in a Docker container
Enterprise Edition

Neo4j supports clustering in a containerized environment without an orchestration tool. This tutorial walks through setting this up locally for testing purposes. For production deployment across multiple servers, see Deploy a Neo4j cluster on multiple Docker hosts.

The examples on this page make use of both command expansion and DNS discovery method. For more information, see:

Deploy a Neo4j cluster using Docker Compose

You can deploy a Neo4j cluster using Docker Compose. Docker Compose is a management tool for Docker containers. You use a YAML file to define the infrastructure of all your cluster servers in one file. Then, by running the single command docker-compose up, you create and start all the members without the need to invoke each of them individually. For more information about Docker Compose, see the Docker Compose official documentation.

Prerequisites

Verify that you have installed Docker Compose. For more information, see the Install Docker Compose official documentation.

Procedure

Create a configuration file neo4j.conf which will be shared across cluster members and make it readable and writable for the user (eg., chmod 640 neo4j.conf)

# Setting that specifies how much memory Neo4j is allowed to use for the page cache.
server.memory.pagecache.size=100M

# Setting that specifies the initial JVM heap size.
server.memory.heap.initial_size=100M

# The behavior of the discovery service is determined by the parameters `dbms.cluster.discovery.resolver_type` and `dbms.cluster.endpoints`
# The DNS strategy fetches the IP addresses of the cluster members using the DNS A records.
dbms.cluster.discovery.resolver_type=DNS

# The value of `dbms.cluster.endpoints` should be set to a single domain name and the port of the discovery service.
# The domain name returns an A record for every server in the cluster when a DNS lookup is performed.
# Each A record returned by DNS should contain the IP address of the server in the cluster.
# The configured server uses all the IP addresses from the A records to join or form a cluster.
# The discovery port must be the same on all servers when using this configuration.
dbms.cluster.endpoints=neo4j-network:6000

# Address (the public hostname/IP address of the machine)
# and port setting that specifies where this instance advertises for discovery protocol messages from other members of the cluster.
server.cluster.advertised_address=$(hostname -i)

# Address (the public hostname/IP address of the machine)
# and port setting that specifies where this instance advertises for Raft messages within the cluster.
server.cluster.raft.advertised_address=$(hostname)

# Enable server-side routing
dbms.routing.enabled=true

# Use server-side routing for neo4j:// protocol connections.
dbms.routing.default_router=SERVER

# The advertised address for the intra-cluster routing connector.
server.routing.advertised_address=$(hostname)

# Automatically enable servers, rather than needing to explicitly do so for Free servers
initial.dbms.automatically_enable_free_servers=true

Prepare your docker-compose.yml file using the following example. For more information, see the Docker Compose official documentation.

Example 1. Example docker-compose.yml file

version: '3.8'

# Custom top-level network
networks:
  neo4j-internal:

services:

  server1:
    # Docker image to be used
    image: ${NEO4J_DOCKER_IMAGE}

    # Hostname
    hostname: server1

    # Service-level network, which specifies the networks, from the list of the top-level networks (in this case only neo4j-internal), that the server will connect to.
    # Adds a network alias (used in neo4j.conf when configuring the discovery members)
    networks:
      neo4j-internal:
        aliases:
          - neo4j-network

    # The ports that will be accessible from outside the container - HTTP (7474) and Bolt (7687).
    ports:
      - "7474:7474"
      - "7687:7687"

    # Uncomment the volumes to be mounted to make them accessible from outside the container.
    volumes:
      - ./neo4j.conf:/conf/neo4j.conf # This is the main configuration file.
      - ./data/server1:/data
      - ./logs/server1:/logs
      - ./conf/server1:/conf
      - ./import/server1:/import
      #- ./metrics/server1:/metrics
      #- ./licenses/server1:/licenses
      #- ./ssl/server1:/ssl

    # Passes the following environment variables to the container
    environment:
      - NEO4J_ACCEPT_LICENSE_AGREEMENT
      - NEO4J_AUTH
      - EXTENDED_CONF
      - NEO4J_EDITION
      - NEO4J_initial_server_mode__constraint=PRIMARY

    # Simple check testing whether the port 7474 is opened.
    # If so, the instance running inside the container is considered as "healthy".
    # This status can be checked using the "docker ps" command.
    healthcheck:
      test: ["CMD-SHELL", "wget --no-verbose --tries=1 --spider localhost:7474 || exit 1"]

    # Set up the user
    user: ${USER_ID}:${GROUP_ID}

  server2:
    image: ${NEO4J_DOCKER_IMAGE}
    hostname: server2
    networks:
      neo4j-internal:
        aliases:
          - neo4j-network
    ports:
      - "7475:7474"
      - "7688:7687"
    volumes:
      - ./neo4j.conf:/conf/neo4j.conf
      - ./data/server2:/data
      - ./logs/server2:/logs
      - ./conf/server2:/conf
      - ./import/server2:/import
      #- ./metrics/server2:/metrics
      #- ./licenses/server2:/licenses
      #- ./ssl/server2:/ssl
    environment:
      - NEO4J_ACCEPT_LICENSE_AGREEMENT
      - NEO4J_AUTH
      - EXTENDED_CONF
      - NEO4J_EDITION
      - NEO4J_initial_server_mode__constraint=PRIMARY
    healthcheck:
      test: ["CMD-SHELL", "wget --no-verbose --tries=1 --spider localhost:7474 || exit 1"]
    user: ${USER_ID}:${GROUP_ID}

  server3:
    image: ${NEO4J_DOCKER_IMAGE}
    hostname: server3
    networks:
      neo4j-internal:
        aliases:
          - neo4j-network
    ports:
      - "7476:7474"
      - "7689:7687"
    volumes:
      - ./neo4j.conf:/conf/neo4j.conf
      - ./data/server3:/data
      - ./logs/server3:/logs
      - ./conf/server3:/conf
      - ./import/server3:/import
      #- ./metrics/server3:/metrics
      #- ./licenses/server3:/licenses
      #- ./ssl/server3:/ssl
    environment:
      - NEO4J_ACCEPT_LICENSE_AGREEMENT
      - NEO4J_AUTH
      - EXTENDED_CONF
      - NEO4J_EDITION
      - NEO4J_initial_server_mode__constraint=PRIMARY
    healthcheck:
      test: ["CMD-SHELL", "wget --no-verbose --tries=1 --spider localhost:7474 || exit 1"]
    user: ${USER_ID}:${GROUP_ID}

  server4:
    image: ${NEO4J_DOCKER_IMAGE}
    hostname: server4
    networks:
      neo4j-internal:
        aliases:
          - neo4j-network
    ports:
      - "7477:7474"
      - "7690:7687"
    volumes:
      - ./neo4j.conf:/conf/neo4j.conf
      - ./data/server4:/data
      - ./logs/server4:/logs
      - ./conf/server4:/conf
      - ./import/server4:/import
      #- ./metrics/server4:/metrics
      #- ./licenses/server4:/licenses
      #- ./ssl/server4:/ssl
    environment:
      - NEO4J_ACCEPT_LICENSE_AGREEMENT
      - NEO4J_AUTH
      - EXTENDED_CONF
      - NEO4J_EDITION
      - NEO4J_initial_server_mode__constraint=SECONDARY
    healthcheck:
      test: ["CMD-SHELL", "wget --no-verbose --tries=1 --spider localhost:7474 || exit 1"]
    user: ${USER_ID}:${GROUP_ID}

Set up the environment variables:
- export USER_ID="$(id -u)"
- export GROUP_ID="$(id -g)"
- export NEO4J_DOCKER_IMAGE=neo4j:enterprise
- export NEO4J_EDITION=docker_compose
- export EXTENDED_CONF=yes
- export NEO4J_ACCEPT_LICENSE_AGREEMENT=yes
- export NEO4J_AUTH=neo4j/your_password

Pre-build the folder structure by running the following command:

mkdir -p conf/{server1,server2,server3,server4} data/{server1,server2,server3,server4} import/{server1,server2,server3,server4} logs/{server1,server2,server3,server4}

Deploy your Neo4j cluster by running docker-compose up from your project folder.
The instance will be available at the following addresses:
- Neo4j instance server1 will be available at http://localhost:7474/.
- Neo4j instance server2 will be available at http://localhost:7475/.
- Neo4j instance server3 will be available at http://localhost:7476/.
- Neo4j instance server4 will be available at http://localhost:7477/.
Authenticate with the default neo4j/your_password credentials.
Check the status of the cluster by running the following in Neo4j Browser:
```
SHOW SERVERS
```
Example output:

Deploy a Neo4j Cluster using environment variables

You can set up containers in a cluster to talk to each other using environment variables. Each container must have a network route to each of the others, the NEO4J_initial_dbms_default__primaries__count, NEO4J_initial_dbms_default__secondaries__count, and NEO4J_dbms_cluster_endpoints environment variables must be set for all servers.

Cluster environment variables

The following environment variables are specific to the Neo4j cluster, and are available in the Neo4j Enterprise Edition:

NEO4J_initial_server_mode__constraint: the database mode, defaults to NONE, can be set to PRIMARY or SECONDARY.
NEO4J_dbms_cluster_endpoints: a comma-separated list of endpoints, which a server should contact to discover other cluster servers.
NEO4J_server_cluster_advertised__address: hostname/IP address and port to advertise for transaction handling and discovery service.
NEO4J_server_cluster_raft_advertised__address: hostname/IP address and port to advertise for cluster communication.

See Configuration settings for more details of Neo4j cluster settings.

Set up a Neo4j Cluster on a single Docker host

Within a single Docker host, you can use the default ports for HTTP, HTTPS, and Bolt. For each container, these ports are mapped to a different set of ports on the Docker host.

Example of a docker run command for deploying a cluster with three servers:

docker network create --driver=bridge neo4j-cluster

docker run --name=server1 --detach --network=neo4j-cluster \
    --publish=7474:7474 --publish=7473:7473 --publish=7687:7687 \
    --hostname=server1 \
    --env NEO4J_initial_server_mode__constraint=PRIMARY \
    --env NEO4J_dbms_cluster_endpoints=server1:6000,server2:6000,server3:6000 \
    --env NEO4J_ACCEPT_LICENSE_AGREEMENT=yes \
    --env NEO4J_server_bolt_advertised__address=localhost:7687 \
    --env NEO4J_server_http_advertised__address=localhost:7474 \
    --env NEO4J_AUTH=neo4j/your_password \
    neo4j:2026.08.1-enterprise

docker run --name=server2 --detach --network=neo4j-cluster \
    --publish=8474:7474 --publish=8473:7473 --publish=8687:7687 \
    --hostname=server2 \
    --env NEO4J_initial_server_mode__constraint=PRIMARY \
    --env NEO4J_dbms_cluster_endpoints=server1:6000,server2:6000,server3:6000 \
    --env NEO4J_ACCEPT_LICENSE_AGREEMENT=yes \
    --env NEO4J_server_bolt_advertised__address=localhost:8687 \
    --env NEO4J_server_http_advertised__address=localhost:8474 \
    --env NEO4J_AUTH=neo4j/your_password \
    neo4j:2026.08.1-enterprise

docker run --name=server3 --detach --network=neo4j-cluster \
    --publish=9474:7474 --publish=9473:7473 --publish=9687:7687 \
    --hostname=server3 \
    --env NEO4J_initial_server_mode__constraint=PRIMARY \
    --env NEO4J_dbms_cluster_endpoints=server1:6000,server2:6000,server3:6000 \
    --env NEO4J_ACCEPT_LICENSE_AGREEMENT=yes \
    --env NEO4J_server_bolt_advertised__address=localhost:9687 \
    --env NEO4J_server_http_advertised__address=localhost:9474 \
    --env NEO4J_AUTH=neo4j/your_password \
    neo4j:2026.08.1-enterprise

Additional servers can be added to the cluster in an ad-hoc fashion.

Example of a docker run command for adding a fourth server with a role SECONDARY to the cluster:

docker run --name=read-server4 --detach --network=neo4j-cluster \
    --publish=10474:7474 --publish=10473:7473 --publish=10687:7687 \
    --hostname=read-server4 \
    --env NEO4J_initial_server_mode__constraint=SECONDARY \
    --env NEO4J_dbms_cluster_endpoints=server1:6000,server2:6000,server3:6000 \
    --env NEO4J_ACCEPT_LICENSE_AGREEMENT=yes \
    --env NEO4J_server_bolt_advertised__address=localhost:10687 \
    --env NEO4J_server_http_advertised__address=localhost:10474 \
    neo4j:2026.08.1-enterprise

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).