Clustering glossary

Term Description

Term	Description
Allocator	A component in the cluster that allocates databases to servers according to the topology constraints specified and an allocation strategy.
Asynchronous replication	Enables efficient scale-out of secondary database copies but offers no guarantees under fault conditions. The data present in the secondary copy is not guaranteed to be up-to-date with a majority of the database’s primary copies.
Availability	The ability to access data in a database. A database can be available for read-write, read-only, or altogether unavailable. A clustered database is fault-tolerant, i.e. it can maintain both read and write availability if some primaries fail (see Fault tolerance for more information). If the number of failed primaries exceeds the fault tolerance limit, the database becomes read-only. Should all copies fail, the database becomes unavailable.
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.
Causal consistency	When a client (driver) creates a session and executes a query, the responding server issues the client a bookmark. This reflects the state of the database copy on that server at the time the query was executed. The bookmark is passed along and updated by all subsequent queries in the session, regardless of which server executes what query. A bookmark can only be updated monotonically increasing. If a server is behind the state in the bookmark, it waits until it has caught up, or time out the query. Thus, clients executing queries within a session are guaranteed to read their own writes, and only see successively later states of the database. This is sometimes also referred to as session consistency.
Cluster	A collection of servers running Neo4j that are configured to communicate with each other. These may be used to host databases and the databases may be configured to replicate across servers in the cluster thus achieving read scalability or high availability. A minimum of three servers is required for the cluster to be fault-tolerant.
Database	The data store for the nodes, relationships, and properties that make up the graph. Multiple databases can be hosted on a Database Management Server (DBMS).
Database Management System (DBMS)	The Neo4j services and system database running on an instance of a single server or cluster to provide one or more databases.
Deallocate	An act of safely removing (i.e. without loss of data or reduced fault tolerance) a database from a server, or removing a server from a cluster.
Disaster recovery	A manual intervention to restore availability of a cluster, or databases within a cluster.
Election	In the event that a leader becomes unresponsive, followers automatically trigger an election and vote for a new leader. A majority is required for the vote to be successful.
Fault tolerance	A guarantee that a database can maintain persistence and availability in the event of one or more failures. The number of failures `f` that can be tolerated is dependent on the number of primaries `n` for the database and follows the formula `f = (n-1)/2`. In the event that more than `f` primaries fail, the database can no longer process write transactions and becomes read-only.
Follower	A primary copy of a database acting as a follower, receives and acknowledges synchronous writes from the leader.
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. Each database can have a different leader within the cluster.
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.
Read scaling	Adding secondary copies of the database to the cluster can offload read queries from the primary databases and thus reduce the load and aid write performance of the cluster.
Secondary	An asynchronously replicated copy of the database that provides read scaling within the cluster. It is also suitable for running graph analytic workloads in a cluster using Graph Data Science and taking backups without incurring load on the primary.
Seed	A file used to create a copy of a database on a single instance or on a member of a cluster. This can be a database dump or a database backup. Seed can also be used as a verb to describe the act seeding a cluster from a backup.
Server	A physical machine, a virtual machine, or a container running Neo4j DBMS. The server can be standalone or part of a cluster.
Session consistency	An alternative name for Neo4j’s causal consistency.
Standalone server	A single server, or container, running Neo4j DBMS and not part of a cluster.
Synchronous replication	When attempting to commit a transaction, the leader primary replicates the transaction and block, requiring the follower primaries to acknowledge the replication before allowing the commit to proceed. This blocking replication is known as synchronous, and ensures data durability and consistency within the cluster. See also asynchronous replication.
Topology	A configuration that describes how the copies of a database should be spread across the servers in a cluster.

Allocator

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

Asynchronous replication

Enables efficient scale-out of secondary database copies but offers no guarantees under fault conditions. The data present in the secondary copy is not guaranteed to be up-to-date with a majority of the database’s primary copies.

Availability

The ability to access data in a database. A database can be available for read-write, read-only, or altogether unavailable. A clustered database is fault-tolerant, i.e. it can maintain both read and write availability if some primaries fail (see Fault tolerance for more information). If the number of failed primaries exceeds the fault tolerance limit, the database becomes read-only. Should all copies fail, the database becomes unavailable.

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.

Causal consistency

When a client (driver) creates a session and executes a query, the responding server issues the client a bookmark. This reflects the state of the database copy on that server at the time the query was executed. The bookmark is passed along and updated by all subsequent queries in the session, regardless of which server executes what query. A bookmark can only be updated monotonically increasing. If a server is behind the state in the bookmark, it waits until it has caught up, or time out the query. Thus, clients executing queries within a session are guaranteed to read their own writes, and only see successively later states of the database. This is sometimes also referred to as session consistency.

Cluster

A collection of servers running Neo4j that are configured to communicate with each other. These may be used to host databases and the databases may be configured to replicate across servers in the cluster thus achieving read scalability or high availability. A minimum of three servers is required for the cluster to be fault-tolerant.

Database

The data store for the nodes, relationships, and properties that make up the graph. Multiple databases can be hosted on a Database Management Server (DBMS).

Database Management System (DBMS)

The Neo4j services and system database running on an instance of a single server or cluster to provide one or more databases.

Deallocate

An act of safely removing (i.e. without loss of data or reduced fault tolerance) a database from a server, or removing a server from a cluster.

Disaster recovery

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

Election

In the event that a leader becomes unresponsive, followers automatically trigger an election and vote for a new leader. A majority is required for the vote to be successful.

Fault tolerance

A guarantee that a database can maintain persistence and availability in the event of one or more failures. The number of failures f that can be tolerated is dependent on the number of primaries n for the database and follows the formula f = (n-1)/2. In the event that more than f primaries fail, the database can no longer process write transactions and becomes read-only.

Follower

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

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. Each database can have a different leader within the cluster.

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.

Read scaling

Adding secondary copies of the database to the cluster can offload read queries from the primary databases and thus reduce the load and aid write performance of the cluster.

Secondary

An asynchronously replicated copy of the database that provides read scaling within the cluster. It is also suitable for running graph analytic workloads in a cluster using Graph Data Science and taking backups without incurring load on the primary.

Seed

A file used to create a copy of a database on a single instance or on a member of a cluster. This can be a database dump or a database backup. Seed can also be used as a verb to describe the act seeding a cluster from a backup.

Server

A physical machine, a virtual machine, or a container running Neo4j DBMS. The server can be standalone or part of a cluster.

Session consistency

An alternative name for Neo4j’s causal consistency.

Standalone server

A single server, or container, running Neo4j DBMS and not part of a cluster.

Synchronous replication

When attempting to commit a transaction, the leader primary replicates the transaction and block, requiring the follower primaries to acknowledge the replication before allowing the commit to proceed. This blocking replication is known as synchronous, and ensures data durability and consistency within the cluster. See also asynchronous replication.

Topology

A configuration that describes how the copies of a database should be spread across the servers in a cluster.

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).