A new course is available on GraphAcademy for Building Neo4j Applications with Java! Michael Hunger and I collaborated to create a hands-on course that starts with a project skeleton and guides users through writing code to build a completed IMDB-clone application with Neo4j and Java. In the app, we can store and query users, movies, genres, people, and user favorites.
The data that feeds the fully-fledged application includes the MovieLens recommendation dataset, augmented with themoviedb.org movie and cast data. Data results are presented to the user through a beautiful webpage supported by Vue.js for a user-friendly experience. Many of you might also wonder which Java web framework we chose – so many choices! SparkJava was the winner for this course due to its minimalist approach. We focused on the backend aspects of Java, agnostic of some of the larger web frameworks (such as Spring or Quarkus). Other courses devoted to those specific frameworks may appear, so stay tuned!
If you are interested in similar courses for other languages, check out the full course list on GraphAcademy, and if there’s something missing you’d like to see, don’t hesitate to let us know. We hope you enjoy building fun and useful things with Neo4j – we definitely do!
FEATURED COMMUNITY MEMBER: Sebastian Daschner
ARTICLE: Building a Full Stack IMDB Clone with a Java Backend Using SparkJava and Neo4jJennifer Reif and Michael Hunger explain some of the choices they made while implementing a Neo4j GraphAcademy course, Building Neo4j Applications with Java, for a Java backend.
FREE TRAINING: Intermediate Cypher QueriesOnce you complete the Cypher Fundamentals course, you can take this intermediate course to learn about more complex patterns and features of Cypher. You will take a deeper look at more advanced queries using the recommendation dataset with Person, Movie, Genre, and User nodes.
NEO4J LIVE: Interactive Dashboards
BLOG: New York Times Article Knowledge GraphMichael Hunger analyzes a data set of New York Times articles using the NYTimes API to access the article metadata. He explores relationships in those articles, such as topic overlap and recommendations.
DEMO: Building Intelligent Supply Chain Application with Neo4jIn this blog, Tara Jana shows you how to build a globally distributed, scalable enterprise supply chain application using Neo4j, focusing on fleet management and warehouse distribution center mechanics.
UNDER THE HOOD: How to Manage Complexity to Extract KnowledgeIn this new episode, Chris Gioran explains how to gain insights from complex datasets by extracting knowledge at the data model level. He walks you through an example of user recommendations to identify and resolve friction points that may appear between the application and the database.
TWEET OF THE WEEK: @colinwrenDon’t forget to retweet if you like it!
Continuing the proof of concept I've been doing for https://t.co/aanLEAGJEi with Neo4J & GraphQL. I built a simple Figma plugin that allows objects in Figma to be linked to User Stories and using the Product Knowledge Graph I can return the tests that cover that screen pic.twitter.com/jKs1meT1RY— Colin Wren (@colinwren) April 17, 2022
WHAT ELSE IS GOING ON?
If you’re a data scientist looking to do some really fun work on graph embeddings, GDS, and graph ML pipelines, please contact David Allen on LinkedIn.
Watch the deep dive into the Neo4j PHP client with Ghlen Nagels, founder of Laudis, and Florent Biville.
Webinar: What’s New in Graph Data Science: Faster and Easier Than Before – North America is on April 26.