Plugins

This page describes how to install plugins into a Neo4j instance running inside a Docker container. For instructions about plugins in general see Configuration → Plugins.

Installing plugins

To install plugins, including user-defined procedures, mount the folder or volume containing the plugin JARs to /plugins, for example:

docker run \
   --publish=7474:7474 --publish=7687:7687 \
   --volume=$HOME/neo4j/plugins:/plugins \
   neo4j:2026.08.1

Neo4j automatically loads any plugins found in the /plugins folder on startup.

`NEO4J_PLUGINS` utility

The Neo4j Docker image includes a startup script that can automatically download and configure certain Neo4j plugins at runtime.

This feature is intended to facilitate the use of the Neo4j plugins in development environments, but it is not recommended for production environments.

To use plugins in production with Neo4j Docker containers, see Install user-defined procedures.

The NEO4J_PLUGINS environment variable can be used to specify the plugins to install using this method. This should be set to a JSON-formatted list of the supported plugins.

If invalid NEO4J_PLUGINS values are passed, Neo4j returns a notification that the plugin is not known. For example, --env NEO4J_PLUGINS='["gds"]' returns the following notification:

Example output

"gds" is not a known Neo4j plugin. Options are:
apoc
apoc-extended
bloom
genai
graph-data-science
n10s

Install the APOC Core plugin (`apoc`)

You can use the Docker argument --env NEO4J_PLUGINS='["apoc"]' and run the following command:

docker run -it --rm \
  --publish=7474:7474 --publish=7687:7687 \
  --env NEO4J_AUTH=none \
  --env NEO4J_PLUGINS='["apoc"]' \
  neo4j:2026.08.1

Install the APOC Core plugin (`apoc`) and the Graph Data Science plugin (`graph-data-science`)

You can use the Docker argument --env NEO4J_PLUGINS='["apoc", "graph-data-science"]' and run the following command:

docker run -it --rm \
  --publish=7474:7474 --publish=7687:7687 \
  --env NEO4J_AUTH=none \
  --env NEO4J_PLUGINS='["apoc", "graph-data-science"]' \
  neo4j:2026.08.1

Storing downloaded plugins

In situations where bandwidth is limited, or Neo4j is stopped and started frequently, it may be desirable to download plugins once and re-use them rather than downloading them each time.

By using the NEO4J_PLUGINS utility in combination with mounting storage to /plugins, the plugin jars are downloaded into the /plugins folder. This can then be used again later to supply the same plugins to Neo4j without needing to set NEO4J_PLUGINS.

Example 1. Example of automatically downloading and re-using plugins with docker.

Get the APOC plugin and save it into $HOME/neo4j/plugins

docker run -it --rm \
  --publish=7474:7474 --publish=7687:7687 \
  --env NEO4J_AUTH=none \
  --env NEO4J_PLUGINS='["apoc"]' \
   --volume=$HOME/neo4j/plugins:/plugins \ (1)
  neo4j:2026.08.1

1	Mounts host folder `$HOME/neo4j/plugins` to `/plugins`.

Verify the apoc plugin is downloaded.

docker kill <containerID/name>
ls $HOME/neo4j/plugins
  apoc.jar

Start a new container and verify apoc is installed.

docker run -it --rm \
  --publish=7474:7474 --publish=7687:7687 \
  --env NEO4J_AUTH=none \
   --volume=$HOME/neo4j/plugins:/plugins \
  neo4j:2026.08.1

cypher-shell "RETURN apoc.version();"

Installing plugin licenses

If a plugin requires a license, the license file can be supplied to the container by mounting the folder or volume containing license file(s) to /licenses.

To check if the plugin requires a license, refer to the general plugin documentation.

Example 2. Installing plugins and licenses by mounting folders to the container

docker run \
   --publish=7474:7474 --publish=7687:7687 \
   --volume=$HOME/neo4j/plugins:/plugins \   (1)
   --volume=$HOME/neo4j/licenses:/licenses \ (2)
   neo4j:2026.08.1

1	folder containing plugin jars.
2	folder containing license files.

The licenses must also be provided if using the NEO4J_PLUGINS utility to install the plugins.

Example 3. Installing plugins and licenses by mounting folders to the container using NEO4J_PLUGINS utility

docker run \
   --publish=7474:7474 --publish=7687:7687 \
   --env NEO4J_PLUGINS='["bloom"]' \
   --volume=$HOME/neo4j/licenses:/licenses \ (1)
   neo4j:2026.08.1

1	A folder containing license files.

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).