Monitor replication status
Enterprise Edition

The dbms.cluster.statusCheck() procedure can be used to monitor the ability to replicate in clustered databases. In most cases this means a clustered database is write available. The procedure identifies which members of a clustered database are up-to-date and can participate in successful replication. Therefore, it is useful in determining the fault tolerance of a clustered database. Additionally, you can use the procedure to identify the leader of a clustered database within the cluster.

The procedure replicates a dummy transaction within the cluster and verifies that it can be replicated and applied. Since the status check does not replicate an actual transaction, it does not guarantee write availability, as other factors in the write path (e.g., database issues) may block transactions. However, a healthy status typically indicates write availability in most cases.

Cluster status check

Syntax

CALL dbms.cluster.statusCheck(databases :: LIST<STRING>, timeoutMilliseconds = null :: INTEGER)

Input arguments

Name Type Description

databases

List<String>

Databases for which the status check should run. Providing an empty list runs the status check for all clustered databases on that server, i.e. it does not run on singles or secondaries.

timeoutMilliseconds

Integer

Specifies the maximum wait time for replication before marking it unsuccessful. Default value is 1000 milliseconds.

Return arguments

The procedure returns a row for all primary members of all the requested databases where each row consists of:

Name Type Description

database

String

The database for which a status check entry was replicated.

serverId

String

The UUID of the server, which did or did not participate in a successful replication of the status check entry.

serverName

String

The friendly name of the server, or its UUID if no name is set.

address

String

The address of the Bolt port for the server.

replicationSuccessful

Boolean

Indicates if the server (on which the procedure is run) can replicate a transaction.

memberStatus

String

The status of each primary member.

recognisedLeader

String

The server id of the perceived leader of each primary member.

recognisedLeaderTerm

Integer

The term of the perceived leader of each primary member. If the members report different leaders, the one with the highest term should be trusted.

requester

Boolean

Whether a server is the requester or not.

error

String

Contains any error message if present. An example of an error is that one or more of the requested databases do not exist on the requester.

Possible values of replicationSuccessful

  • TRUE — if this server managed to replicate the dummy transaction to a majority of cluster members within the given timeout.

  • FALSE — if it failed to replicate within the timeout. The value is the same column-wise. A failed replication can either indicate a real issue in the cluster (e.g., no leader) or that this server is too far behind in applying updates and can’t replicate.

Possible values of memberStatus

  • APPLYING means that the member can replicate and is actively applying transactions.

  • REPLICATING means that the member can participate in replicating but cannot apply. This state is uncommon, but may happen while waiting for the database to start and accept transactions.

  • UNAVAILABLE means that the member is either too far behind the leader or unreachable. They are unhealthy and cannot add to the fault-tolerance.

Possible values of requester

  • TRUE — for the server on which the procedure is run.

  • FALSE — on the remaining servers.

In general, you can use the replicationSuccessful field to determine overall write-availability, whereas the memberStatus field can be checked in order to see whether the database is fault-tolerant or not.

Example

Running the status check

When running the cluster status check against a server, expect similar output to the following:

+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| database | serverId                               | serverName                             | address          | replicationSuccessful | memberStatus | recognisedLeader                       | recognisedLeaderTerm | requester | error |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "neo4j"  | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | "localhost:7682" | TRUE                  | "APPLYING"   | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | 4                    | FALSE     | NULL  |
| "neo4j"  | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | "localhost:7681" | TRUE                  | "APPLYING"   | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | 4                    | TRUE      | NULL  |
| "neo4j"  | "58c70f4b-910d-4d0e-b0f2-3084554079ec" | "58c70f4b-910d-4d0e-b0f2-3084554079ec" | "localhost:7683" | TRUE                  | "APPLYING"   | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | 4                    | FALSE     | NULL  |
| "system" | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | "565130e8-b8f0-41ad-8f9d-c660bd8d5519" | "localhost:7681" | TRUE                  | "APPLYING"   | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | 1                    | TRUE      | NULL  |
| "system" | "58c70f4b-910d-4d0e-b0f2-3084554079ec" | "58c70f4b-910d-4d0e-b0f2-3084554079ec" | "localhost:7683" | TRUE                  | "APPLYING"   | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | 1                    | FALSE     | NULL  |
| "system" | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | "localhost:7682" | TRUE                  | "APPLYING"   | "d3fe2e6a-494d-4ab8-81b1-7de2ce31ce11" | 1                    | FALSE     | NULL  |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

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).