Apache Hop for imports into Neo4j

https://www.know-bi.be/blog/tutorial-import-relational-data-into-neo4j-with-graph-output
https://www.know-bi.be/blog/5-minutes-to-get-started-with-apache-hop

5 minutes to get started with Apache Hop
Originally posted on Apr 5, 2022 11:00:00 AM
Last updated on October 1, 2024

Bart Maertens

data architect and developer with over 20 years of experience in data engineering and analytics. Founder and lead of the know.bi expert team, Apache Hop co-founder and PMC member.

5 minutes to get started with Apache Hop

What is Apache Hop?

Apache Hop is a visual, metadata-driven data engineering platform that allows data professionals to build and run data pipelines without the need to write code.

Apache Hop was designed and built to support data projects throughout the entire life cycle, from the moment a data point arrives in your organization until it lands in your data warehouse or analytics platform.

Apache Hop has built-in support for hundreds of source and target data platforms. This includes file format, relational, graph and NoSQL databases and many others. Apache Hop is built to process any volume of data: from edge devices in IoT projects over standard data warehousing projects up to distributed platforms that process petabytes of data.

Why Apache Hop?
Hop users visually develop pipelines and workflows using metadata to describe how data should be processed. This visual design enables data developers to focus on what they want to do, without the need to spend countless hours on technical details.

This visual design and the abstraction of the technical details enable data professionals to be more productive. Visual design makes citizen developers more productive when developing data pipelines and workflows than they would be with "real" source code. Even more so, maintaining and updating your own (or even worse, someone else's) workflows and pipelines after a couple of weeks of months is a lot easier when you can visually see the flow of data in the pipeline.

5 steps to a successful Apache Hop project

As with any platform or any project, a good start is half the battle. Hop has all the functionality required to organize your work in projects and keep a strict separation between code (project) and configuration (environments and environments files).

Setting up your Hop projects according to the best practices described below will make your projects easier to develop, maintain, and deploy.

Whether you have previous experience with Pentaho Data Integration (Kettle) and want to upgrade to Apache Hop or are new to Apache Hop, no matter how far you are in adopting a DevOps way of working, a well-designed project and corresponding environments will make your life a lot easier.

Rather than just diving in and creating workflows and pipelines, here are 5 steps you should follow to start working with Hop.