Pipelines at Scale - Soundwave Sessions

What this episode covers

This podcast explores how to build scalable graph data pipelines by integrating Apache Spark with Neo4j for large-scale data processing and analytics. It discusses data ingestion, transformation, distributed computation, and best practices for moving data efficiently into graph structures. Perfect for data engineers, big data architects, software developers, and professionals working with large-scale connected data systems.

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Frequently Asked Questions

How long is this episode of Soundwave Sessions?

This episode is 47 minutes long.

When was this Soundwave Sessions episode published?

This episode was published on June 2, 2026.

What is this episode about?

This podcast explores how to build scalable graph data pipelines by integrating Apache Spark with Neo4j for large-scale data processing and analytics. It discusses data ingestion, transformation, distributed computation, and best practices for...

Can I download this Soundwave Sessions episode?

Yes, you can download this episode by clicking the download button on the episode player, or subscribe to the podcast in your preferred podcast app for automatic downloads.