Quickstart: Deploy a Neo4j cluster for analytic queries
Enterprise Edition

This quickstart shows how to configure and deploy a special Neo4j cluster that comprises one primary server and N secondary servers to support analytic queries. The primary server handles the transaction workloads, whereas the secondary servers are configured with the Neo4j Graph Data Science library (GDS) and are used only for the analytic workload.
Information on using GDS in a cluster can be found in the Neo4j Graph Data Science library documentation.

The cluster is deployed to a cloud or a local Kubernetes cluster using the Neo4j Helm chart.

Prerequisites

Before you can deploy a Neo4j cluster on Kubernetes, you need to have:

A Kubernetes cluster running and the kubectl command-line tool installed and configured to communicate with your cluster. For more information, see Quickstart: Deploy a cluster → Prerequisites.
A valid license for Neo4j Enterprise Edition. For more information, see Install GDS Enterprise Edition (EE) and Bloom plugins.
The latest version of the Neo4j Helm chart repository.
(Optional) A valid license for GDS Enterprise Edition. To install a licensed plugin, you must provide the license files in a Kubernetes secret. For more information, see Install GDS Enterprise Edition (EE) and Bloom plugins.

Create a value YAML file for each type of server

To set up a Neo4j cluster for analytic queries, you need to create a value YAML file for each type of server, primary and secondary. For example:

Create a value YAML file for the primary server, for example, primary-value.yaml:

neo4j:
  name: analytics-cluster
  acceptLicenseAgreement: "yes"
  edition: enterprise
  password: my-password
volumes:
  data:
    mode: defaultStorageClass

# Disable the Neo4j load balancer and enable the internal service so that the servers can access each other:
services:
  neo4j:
    enabled: false
  internals:
    enabled: true

# Enable the analytics cluster and set the type to primary:
analytics:
  enabled: true
  type:
    name: primary

Create a value YAML file for the secondary servers, for example, secondary-gds.yaml. The password must be the same as for the primary server. If you are using GDS Enterprise Edition, you also need to create a secret with the license file and mount it as the /licenses volume mount. For more information on how to create a secret, see Install GDS Enterprise Edition (EE) and Bloom plugins.

neo4j:
  name: analytics-cluster
  acceptLicenseAgreement: "yes"
  edition: enterprise
  password: my-password
volumes:
  data:
    mode: defaultStorageClass
  # Define the volume mount for the license file:
  licenses:
    disableSubPathExpr: true
    mode: volume
    volume:
      secret:
        secretName: gds-license
        items:
          - key: gds.license
            path: gds.license

# Set the environment variables to download the plugins:
env:
  NEO4J_PLUGINS: '["graph-data-science"]'

# Set the configuration for the plugins directory and the mount for the license file:
config:
  gds.enterprise.license_file: "/licenses/gds.license"
  server.directories.plugins: "plugins"

# Disable the Neo4j load balancer and enable the internal service so that the servers can access each other:
services:
  neo4j:
    enabled: false
  internals:
    enabled: true

# Enable the analytics cluster and set the type to secondary:
analytics:
  enabled: true
  type:
    name: secondary

For all available options, see Customizing a Neo4j Helm chart.

Install the servers

Install a single Neo4j server using the neo4j-primary.yaml file, created in the previous section:
```
helm install primary neo4j/neo4j -f /path/to/neo4j-primary.yaml
```
Install the first secondary server using the secondary-gds.yaml file, created in the previous section:
```
helm install gds1 neo4j/neo4j -f /path/to/secondary-gds.yaml
```
Repeat step 2 to deploy a second secondary server. Use a different name, for example, gds2.

Verify that the GDS library is installed and licensed

Connect to each of the gds pods using the kubectl exec command:
```
kubectl exec -it gds1-0 -- bash
```

From the bin folder, connect to the system database of the gds1 server using the cypher-shell command:

cypher-shell -u neo4j -p my-password -d system -a bolt://gds1-internals.default.svc.cluster.local:7687

Run the following Cypher function to verify that the GDS library is installed:
```
RETURN gds.version();
```
Call gds.isLicensed() to verify that the GDS library is licensed:
```
RETURN gds.isLicensed();
```
The returned value must be true.

Verify the cluster formation

To verify that the cluster is deployed and running, you can install a load balancer and access Neo4j from the Neo4j Browser.

Deploy a Neo4j load balancer to the same namespace as the Neo4j cluster:

helm install lb neo4j/neo4j-load-balancer --set neo4j.name="analytics-cluster"

When deployed, copy the EXTERNAL_IP of the LoadBalancer service. For more information, see Access the Neo4j cluster from outside Kubernetes.
In a web browser, open the Neo4j Browser at http://EXTERNAL_IP:7474/browser and log in using the password you have configured in your values YAML files.

Verify that the cluster is deployed and running:

SHOW SERVERS;

+------------------------------------------------------------------------------------------------------------------------------------------+
| name                                   | address                                  | state     | health      | hosting                    |
+------------------------------------------------------------------------------------------------------------------------------------------+
| "16cd6e9c-aa5a-4737-8ed5-e0df36ce52d3" | "gds2.default.svc.cluster.local:7687"    | "Free"    | "Available" | ["system"]                 |
| "bafbe254-a8a2-498d-9b60-6b3fd0124045" | "primary.default.svc.cluster.local:7687" | "Enabled" | "Available" | ["neo4j", "system"]		     |
| "f1478d5d-1718-4430-a9b6-26fe9695ca30" | "gds1.default.svc.cluster.local:7687"    | "Free"    | "Available" | ["system"]                 |
+------------------------------------------------------------------------------------------------------------------------------------------+

The output shows that the secondary servers are in state free and host only the system database.

Enable the secondary servers to support analytic queries

To support analytic queries on the secondary servers, you need to enable them and change the neo4j database topology to include them.

In Neo4j Browser, enable the secondary servers to support analytic queries:

ENABLE SERVER "f1478d5d-1718-4430-a9b6-26fe9695ca30";
ENABLE SERVER "16cd6e9c-aa5a-4737-8ed5-e0df36ce52d3";

Alter the database topology to include the secondary servers:
```
ALTER DATABASE neo4j SET TOPOLOGY 1 PRIMARY 2 SECONDARY;
```

Check the status of the neo4j database to confirm the change:

SHOW DATABASE neo4j;

+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| name    | type       | aliases | access       | address                                  | role        | writer | requestedStatus | currentStatus | statusMessage | default | home | constituents |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "neo4j" | "standard" | []      | "read-write" | "primary.default.svc.cluster.local:7687" | "primary"   | TRUE   | "online"        | "online"      | ""            | TRUE    | TRUE | []           |
| "neo4j" | "standard" | []      | "read-write" | "gds1.default.svc.cluster.local:7687"    | "secondary" | FALSE  | "online"        | "online"      | ""            | TRUE    | TRUE | []           |
| "neo4j" | "standard" | []      | "read-write" | "gds2.default.svc.cluster.local:7687"    | "secondary" | FALSE  | "online"        | "online"      | ""            | TRUE    | TRUE | []           |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

Check the status of all servers:

SHOW SERVERS;

+------------------------------------------------------------------------------------------------------------------------------------------+
| name                                   | address                                  | state     | health      | hosting                    |
+------------------------------------------------------------------------------------------------------------------------------------------+
| "16cd6e9c-aa5a-4737-8ed5-e0df36ce52d3" | "gds2.default.svc.cluster.local:7687"    | "Enabled" | "Available" | ["neo4j", "system"]        |
| "bafbe254-a8a2-498d-9b60-6b3fd0124045" | "primary.default.svc.cluster.local:7687" | "Enabled" | "Available" | ["neo4j", "system"]        |
| "f1478d5d-1718-4430-a9b6-26fe9695ca30" | "gds1.default.svc.cluster.local:7687"    | "Enabled" | "Available" | ["neo4j", "system"]        |
+------------------------------------------------------------------------------------------------------------------------------------------+

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).

Quickstart: Deploy a Neo4j cluster for analytic queriesEnterprise Edition