Loading data into Neo4j often starts with a number of simple scripts. As your project grows, so does the number and size of your scripts: they quickly become hard to scale, hard to manage, and hard to maintain.

Apache Hop is a new open-source data orchestration platform that was designed from the ground up to tackle these problems. In Hop, data developers visually design data pipelines that can run on the Hop native engine, or on Spark, Flink, Google Dataflow over Apache Beam.

Hop has built-in life cycle management functionality to help you manage your projects and environments, version control with git, run unit tests, and more.

Apache Hop is unparalleled in its support for Neo4j with over 20 plugins to design, write, and read from your graphs.

What you’ll learn in this webinar:

  • What is Apache Hop and how it works
  • How to load data into and extract data from Neo4j with Apache Hop
  • How Apache Hop pipelines scale with any workload and volume of data
  • How Apache Hop handle data lineage, unit testing, version control, deployment life cycle, and much more

Bart Maertens
Managing Partner at know.bi

Data geek, co-founder of Apache Hop, and founder of know.bi. We help our customers to build solutions with best-in-breed technology.

Markus Kubicek
Daimler


Philipp Zacharias
Daimler


Stefan Kolmar
VP Field Engineering EMEA & APAC, Neo4j


Bruno Ungermann
Country Manager Deutschland, Neo4j

 

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