Neo4j Connector for Apache Spark

Neo4j Connector for Apache Spark is an integration tool that bi-directionally moves and reshapes data between the Neo4j graph platform and Apache Spark™ and opens up the vast Spark Ecosystem to Neo4j.

Enormous amounts of data from various sources are aggregated and transformed in Spark, and there’s considerable value in hooking into these assets.

The Neo4j Connector for Apache Spark reshapes data from tables to graphs and feeds it into Neo4j workflows. Neo4j provides advanced graph capabilities to the Spark ecosystem so businesses can use contextual information to improve forecasting, analytics and predictions.

Bi-directionality of the connector ensures graph-enriched data is transferred to high-value tasks in Spark, like machine learning, without having to rework existing pipelines.

Neo4j Connector for Apache Spark Benefits

  • Rapid access to any data connected to Apache Spark
  • Fast and efficient upload of data between Neo4j and Apache Spark
  • Flexibility to shape and load only data that is needed - and when it is needed
  • Ease-of-use for Neo4j and Apache Spark Developers and Data Scientists

Neo4j Connector for Apache Spark is available for free with full support provided to Neo4j Enterprise Edition customers.

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Blog Post
Announcing Neo4j Connector for Apache Spark
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Video
Create a Graph Data Pipeline With Apache Spark and Neo4j
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Developer Guide
Neo4j Connector for Apache Spark Developer Guide