Neo4j Nodestream Plugin for Nodestream
This plugin provides a Nodestream interface to Neo4j.
Installation
pip install nodestream-plugin-neo4j
Usage
# nodestream.yaml
targets:
neo4j:
database: neo4j
uri: bolt://localhost:7687
username: neo4j
password: neo4j
database_name: neo4j # optional; name of the database to use.
use_enterprise_features: false # optional; use enterprise features (e.g. node key constraints)
Extractor
The Neo4jExtractor class represents an extractor that reads records from a Neo4j database. It takes a single Cypher query as
input and yields the records read from the database. The extractor will automatically paginate through the database until it reaches the end. Therefore, the query needs to include a SKIP and LIMIT clause. For example:
- implementation: nodestream_plugin_neo4j.extractor:Neo4jExtractor
arguments:
query: MATCH (p:Person) WHERE p.name = $name RETURN p.name SKIP $offset LIMIT $limit
uri: bolt://localhost:7687
username: neo4j
password: neo4j
database_name: my_database # Optional; defaults to neo4j
limit: 100000 # Optional; defaults to 100
parameters:
# Optional; defaults to {}
# Any parameters to be passed to the query
# For example, if you want to pass a parameter called "name" with the value "John Doe", you would do this:
name: John Doe
The extractor will automatically add the SKIP and LIMIT clauses to the query. The extractor will also automatically add the offset and limit parameters to the query. The extractor will start with offset set to 0 and limit set to 100 (unless overridden by setting limit) The extractor will continue to paginate through the database until the query returns no results.
Copy Command
The nodestream copy command copies nodes and relationships from one Neo4j target to another. The Neo4j plugin exposes the following --retriever-option parameters to tune throughput.
Retriever options (--retriever-option key=value)
| Option | Type | Default | Description |
|---|---|---|---|
limit |
int | 100 | Page size for each paginated Cypher query (SKIP $offset LIMIT $limit). Larger values mean fewer round-trips. |
shard_size |
int | — | When set, each relationship type is split into shards of this size and fetched concurrently. Requires a key field or falls back to elementId. |
sample_ratio |
int | — | Only copy records where toInteger(split(elementId(r), ':')[-1]) % sample_ratio = 0. A deterministic, reproducible subset. 1 is treated as disabled. |
latest_hours |
int | — | Only copy records where last_ingested_at >= now() - latest_hours. Useful for incremental copies. |
relationships_only |
bool | false | Skip node fetching entirely; only copy relationships. |
Connector options (--connector-option key=value)
| Option | Type | Default | Description |
|---|---|---|---|
chunk_size |
int | target default | Number of records per Cypher write batch inside each flush lane. |
execute_chunks_in_parallel |
bool | false | Run write chunks concurrently within each flush lane. |
retries_per_chunk |
int | 0 | Number of times to retry a failed write chunk before raising. |
Best-known configuration (relationships, 24 h incremental)
Benchmark result: ~27 min, ~776 relationships/s peak for a production graph with ~1.27 M relationships (2026-06-24, sample_ratio=100).
nodestream copy \
--from <source> \
--to <destination> \
--all \
--retriever-option relationships_only=true \
--retriever-option latest_hours=24 \
--retriever-option shard_size=10000 \
--concurrency-limit 20 \
--flush-concurrency 8 \
--batch-size 100000 \
--step-outbox-size 2000000 \
--reporting-frequency 30 \
--connector-option execute_chunks_in_parallel=true \
--connector-option chunk_size=10000 \
--connector-option retries_per_chunk=5 \
--metrics-interval-in-seconds 30 \
--json
Why these values:
shard_size=10000— splits large relationship types into independent coroutines, filling all concurrency slots.concurrency-limit=20— higher values (e.g. 30–40) cause SessionExpired/network errors on the destination; 20 gives 0–50 errors vs. 200+ at 30.flush-concurrency=8— 8 parallel write lanes; saturates destination write throughput without overloading connections.batch-size=100000— larger batches amortise per-batch overhead; peak throughput higher than 50K batches.step-outbox-size=2000000— large buffer so the extractor is never blocked waiting for the writer to drain.relationships_only=true+latest_hours=24— incremental mode; nodes are stable, only new/changed relationships need copying.
Concepts
Migrations
The plugin supports migrations. Migrations are used to create indexes and constraints on the database.
As part of the migration process, the plugin will create __NodestreamMigration__ nodes in the database.
This node will have a name property that is set to the name of the migration.
Additionally, the plugin will create a __NodestreamMigrationLock__ node in the database.
This node will be exit when the migration process is running and will be deleted when the migration process is complete.
This is used to prevent multiple migration processes from running at the same time.
Metadata
Release files for nodestream-plugin-neo4j 0.16.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| nodestream_plugin_neo4j-0.16.0.tar.gz | 23.8 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nodestream_plugin_neo4j-0.16.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 50.1 kB
Release files / nodestream_plugin_neo4j-0.16.0.tar.gz
| Download URL | nodestream_plugin_neo4j-0.16.0.tar.gz |
|---|---|
| Size | 23.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d32495f0ed23086e0c865766bfe7fa300c9515d70420d453b6d7db4f6059eb3e
|
|
BLAKE2b-256 checksum How to use checksums |
f4d43cde2c8fb383bf253ed17ac4cce51cf1a22097d9d9194a09b7f64fba46ff
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 24, 2026.
Transparency logRelease files / nodestream_plugin_neo4j-0.16.0-py3-none-any.whl
| Download URL | nodestream_plugin_neo4j-0.16.0-py3-none-any.whl |
|---|---|
| Size | 26.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a51a5213bc1797d8623bf69744f38615ff0c72bc5b39416157101d38db0cb147
|
|
BLAKE2b-256 checksum How to use checksums |
72d348297e329b353e55415588fe22ef58a62c3d017255b2b613e6649b7bd986
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 24, 2026.
Transparency logSecurity for nodestream-plugin-neo4j 0.16.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for nodestream_plugin_neo4j-0.16.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jun 24, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.