Import

neo4j-admin database import writes CSV data into Neo4j’s native file format as fast as possible.
It also provides support for the Parquet file format.

You should use this command when:

Import performance is important because you have a large amount of data (millions/billions of entities).
The database can be taken offline and you have direct access to one of the servers hosting your Neo4j DBMS.
The database is non-existent or empty and you need to perform the initial data load.
You need to update your graph with a large amount of data, in which case importing data incrementally can be more performant than transactional insertion. For details, see Incremental import in a single command and Incremental import stages.
The CSV data is clean/fault-free (nodes are not duplicated and relationships' start and end nodes exist). neo4j-admin database import can handle data faults but performance is not optimized. If your data has a lot of faults, it is recommended to clean it using a dedicated tool before import.

Other methods of importing data into Neo4j might be better suited to users who primarily work with data in Neo4j rather than manage Neo4j:

Cypher® - CSV data can be bulk loaded via the Cypher command LOAD CSV. See Cypher Manual → LOAD CSV.
Graphical Tools - Neo4j AuraDB → Importing data.

Change Data Capture does not capture any data changes resulting from the use of neo4j-admin database import. See Change Data Capture → Key considerations for more information.

Import command modes

The neo4j-admin database import command has two modes both used for initial data import:

full — used to import data into a non-existent or empty database.
incremental — used when import cannot be completed in a single full import, by allowing the import to be a series of smaller imports.

The user running neo4j-admin database import must have write access to the directories configured by server.directories.data and server.directories.logs.

Starting with Neo4j 2026.03, you can see the detailed logging of import progress for both neo4j-admin database import commands. See Import progress reporting for more details.

Import command memory controls

neo4j-admin database import uses two main memory controls:

JVM heap, configured for the admin process through the usual configuration sources described in Neo4j Admin and Neo4j CLI → Configuration.
Off-heap working memory, controlled by --max-off-heap-memory. If this option is not provided, the importer derives a budget from the available system resources.

The importer does not use the server.memory.pagecache.size configuration setting to size import memory. The off-heap budget is shared across page cache and other off-heap data structures used during import. In dry-run and verbose output, Configured max memory shows the effective off-heap memory budget available to the import command.

Import file considerations

When creating your import files, keep the following in mind:

Fields are comma-separated by default but a different delimiter can be specified.
All files must use the same delimiter.
Multiple data sources can be used for both nodes and relationships.
A data source can optionally be provided using multiple files.
A separate file with a header that provides information on the data fields, must be the first specified file of each data source.
Fields without corresponding information in the header are not read.
UTF-8 encoding is used.
By default, the importer trims extra whitespace at the beginning and end of strings. Quote your data to preserve leading and trailing whitespaces.

Indexes and constraints during import

The creation of indexes and constraints during the import process is supported only by the block format (Enterprise Edition) starting with Neo4j 2025.02. You can use the --schema option to provide a file with Cypher commands to create indexes and constraints during the import process. See Create/Drop indexes and constraints during import for more information.

For other formats or versions prior to 2025.02, you have to add indexes and constraints manually after the import process. See Cypher Manual → Indexes for more information.

Vector indexes can take advantage of the incubated Java Vector API for noticeable speed improvements. If you are using a compatible version of Java, you can uncomment the following value of the server.jvm.additional setting in the neo4j-admin.conf file:

server.jvm.additional=--add-modules=jdk.incubator.vector

Starting with Neo4j 2026.08, the jdk.incubator.vector module is enabled by default. See Changes in Neo4j 2025-2026 for details.

Resuming a stopped or canceled import
Enterprise Edition

An import that is stopped or fails before completing can be resumed from a point closer to where it was stopped. This feature is not supported by block format.

An import can be resumed from the following points:

Linking of relationships
Post-processing

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).