neo4j-spark-connector
A bi-directional connector enabling Apache Spark to read from and write to Neo4j graph databases using Spark DataSource APIs.
What is neo4j-spark-connector?
Neo4j Connector for Apache Spark is an open-source library that enables bi-directional data transfer between Apache Spark and Neo4j graph databases. It allows users to read graph data from Neo4j into Spark DataFrames for distributed processing and write processed results back to Neo4j. This solves the problem of integrating graph database operations with large-scale data analytics pipelines.
Data engineers, data scientists, and developers working with both Apache Spark for big data processing and Neo4j for graph data storage, particularly those building ETL pipelines or performing graph analytics at scale.
Developers choose this connector because it provides a standardized, efficient way to integrate Neo4j with Spark's ecosystem using the DataSource API, eliminating the need for custom integration code. It supports multiple Spark versions and Scala variants, ensuring compatibility with existing Spark deployments.
Overview
Neo4j Connector for Apache Spark, which provides bi-directional read/write access to Neo4j from Spark, using the Spark DataSource APIs
Use Cases
Best For
- Performing large-scale graph analytics using Spark's distributed computing capabilities
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