Bringing Graphs to Your Entire Ecosystem

Graphs help us make sense of connected data and using relationships, we can derive more value from the data we already have. The impact of understanding and leveraging connections is amplified when it’s integrated with your greater ecosystem.

Neo4j offers connectors and integrations to help bring together your most important workflows. From data migration to transformation, you can create a graph data pipeline to enhance existing tooling with graph data or feed data of any shape into Neo4j.

Neo4j Connectors provide scalable, enterprise-ready methods to hook up Neo4j to some of the most popular data orchestration and processing tools. These connectors are fully supported and free to use.

Neo4j Data Warehouse Connector

The Neo4j Data Warehouse Connector offers a simple way to move data between the Neo4j database and data warehouses like Snowflake, Google BigQuery, Amazon Redshift, or Microsoft Azure Synapse Analytics.

Neo4j Connector for Apache Spark 5.0.1

The Neo4j Connector for Apache Spark is an integration tool to move and reshape data bi-directionally between the Neo4j graph platform and Apache Spark. This connector opens up the vast Spark ecosystem to Neo4j.

Neo4j Connector for Apache Kafka 4.1.0

The Neo4j Connector for Apache Kafka integrates Neo4j graphs with Kafka Streams. With this connector, Neo4j can consume any data from Kafka, allowing you to create graphs from streams, and publish data back to Kafka, enabling you to transfer any graph back into a stream.

Neo4j Connector for BI 1.0.10

The Neo4j Connector for BI delivers direct access to Neo4j graph data from business intelligence (BI) tools such as Tableau, Power BI, Looker, TIBCO Spotfire Server, Microstrategy and more.

Neo4j Labs Integrations

The Neo4j Labs team creates a high velocity of graph innovations as a way to test functionality and extensions of our product offerings. These Labs projects are supported via the online community.