Data import
InfinigraphNot available on AuraIntroduced in 2025.12

There are several ways to import data into a sharded property database, depending on your use case and the size of your dataset.

Initial import from delimited files into a sharded property database using neo4j-admin database import full.
Loading data incrementally into an existing sharded property database using neo4j-admin database import incremental.
Importing data using LOAD CSV for small to medium-sized datasets.

For creating a sharded property database from an existing database or backup, see Creating a sharded database from a URI (online) and Resharding databases.

Initial import from delimited files (offline)

You can use the neo4j-admin database import full command to import data from delimited files into a sharded property database as in a standard Neo4j database. This is particularly useful for large datasets that you want to import in bulk before starting your application or for incremental imports later on. You can specify the --property-shard-count option to define the number of property shards you want to create. This will help distribute the data across multiple servers in a Neo4j cluster.

If you are creating the property shards on a self-managed server, the server that executes the neo4j-admin database import command must have sufficient storage space available for all of the property shards that will be created.

Import using S3 (offline)

The following example shows how to import a set of CSV files, back them up to S3 using the --target-location and --target-format options, and then create a database using those seeds in S3. Optionally, you can use the --compress option Introduced in 2026.04 to produce compressed backup artifacts. See Import → Full import for more information.

Using the neo4j-admin database import command, import data into the foo-sharded database, creating one graph shard and three property shards. If the neo4j-admin process is running on the same server as a Neo4j DBMS process, the Neo4j DBMS process must be stopped. The --target-location and --target-format options take the outputs of the import, turn them into uncompressed backups, and upload them to a location ready to be seeded from.
```
neo4j-admin database import full foo-sharded --nodes=nodes.csv --nodes=movies.csv --relationships=relationships.csv --input-type=csv --property-shard-count=3 --schema=schema.cypher --target-location=s3://bucket/folder/ --target-format=backup
```

Create the database foo-sharded as a sharded property database by seeding it from your backups in the AWS S3 bucket:

CREATE DATABASE `foo-sharded`
DEFAULT LANGUAGE CYPHER 25
PROPERTY SHARDS { COUNT 3 }
OPTIONS {
 seedUri: `s3://bucket/folder/`
};

Import using local file system (offline)

You can import data into a Neo4j cluster that has no access to any cloud.

Using the neo4j-admin database import command, import data into the foo-sharded database, creating one graph shard and three property shards. If the neo4j-admin process is running on the same server as a Neo4j DBMS process, the Neo4j DBMS process must be stopped. Optionally, you can use the --compress option Introduced in 2026.04 to produce compressed backup artifacts. See Import → Full import for more information.
```
neo4j-admin database import full foo-sharded --nodes=nodes.csv --nodes=movies.csv --relationships=relationships.csv --input-type=csv --property-shard-count=3 --schema=schema.cypher --target-format=backup
```
Using allow and deny database allocate a single shard to each server in the cluster. See Controlling locations with allowed/denied databases
Move the produced backups from the local file system of the machine used for the import to the servers hosting each of the shards. Each server should have one backup, and the backups must reside in the same path on each server.
On each server, update the neo4j.conf to include the correct settings for file seeding as outlined in Create a database from a URI.

Create the database foo-sharded as a sharded property database by seeding it from your backups in the servers file systems:

CREATE DATABASE `foo-sharded`
DEFAULT LANGUAGE CYPHER 25
PROPERTY SHARDS { COUNT 3 }
OPTIONS {
 seedUri: `file:/backusp/`, seedOptions: 'NO_CHECK'
};

In this context, NO_CHECK prevents the seeding process from verifying that all backups are present on all servers.

The cluster automatically distributes the data across its servers. For more information on seed providers, see Create a database from a URI.

Incremental import / offline updates

You can use the neo4j-admin database import incremental command to import data into an existing database. This is particularly useful for large batches of data that you want to add to an existing sharded property database. It allows you to do faster updates than is possible transactionally.

Stop the foo-sharded database if it is running. See Starting and stopping a sharded property database for instructions.
Run the neo4j-admin database import incremental command by specifying the --property-shard-count option to define the number of property shards you want to create, the --target-location and --target-format options to upload the resulting stores to a location ready for re-creating the databases from, and the CSV files that you wish to update your existing data with. Optionally, you can use the --compress option Introduced in 2026.04 to produce compressed backup artifacts. See Incremental import for more information and instructions.
```
neo4j-admin database import incremental foo-sharded --nodes=nodes.csv --nodes=movies.csv --relationships=relationships.csv --input-type=csv --property-shard-count=3 --schema=schema.cypher --target-location=s3://bucket/folder/ --target-format=backup
```
Re-create your database using the dbms.recreateDatabase() or follow step 2 of Splitting an existing database into shards and creating a new database with the resulting stores the same way you would for a normal offline incremental import.

Importing data using `LOAD CSV` (online)

You can use LOAD CSV to import data into a sharded property database. This is especially useful when you want to import small to medium-sized datasets (up to 10 million records) from local and remote files, including cloud URIs. For more information, see Cypher Manual → LOAD CSV and Getting Started guide → Tutorial: Import CSV data using LOAD CSV.

Transactional Cypher statements involving MERGE or RELATIONSHIP creation have not yet been optimized. Using LOAD CSV will not be performant for anything larger than 100K records.

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).

Data importInfinigraphNot available on AuraIntroduced in 2025.12