Twin4j

This Week in Neo4j: Vector Search, Java, HashGNN, Confluent, Sandbox and more

Senior Developer Marketing Manager

August 26, 2023

2 min read

Welcome to This Week in Neo4j, your weekly fix for news from the world of graph databases!
I hope summer is treating you well (if you live in the northern hemisphere, that is) 🏖️

This week, we announced a milestone feature for Neo4j: Native Vector Search. It provides a simple approach for quickly finding contextually related information by using an algorithm called Hierarchical Navigable Small World (HNSW) to identify similar vectors efficiently. The more similar the vectors, the higher the relevance. Get started with Vector Search.

Cheers,

Alexander Erdl

COMING UP NEXT WEEK!

- Meetup: Unleash the Power of Graphs with AI on August 30, 2023
- Conferences: Meet us at Google Cloud Next on August 29, Copenhagen Developer Festival on August 30 or DataEngBytes Melbourne on August 31
- All Neo4j Events: Webinar, Live demos, and More
- GraphSummit Series: Get Connected With Graphs

FEATURED NODES SPEAKER:
Julian Schibberges

Julian Schibberges works for Bernstein Analytics, part of Bernstein Group, and has worked previously on graph projects in the fields of anti-money laundering an political analysis.
He has co-published two journal articles on a network analysis of United Nations sanction list data on Al-Qaeda/ISIS, providing a new data set for network analysis for political science/security researchers. Connect with him on LinkedIn.

Join him at NODES 2023 where he will explain why understanding political interests is vital in a democratic society, and graphs help us understand those interests better.

JAVA APPLICATION: How to use Spring custom queries and projections

In her previous blog post, Jennifer Reif built a Spring Boot application that connected to a Neo4j AuraDB free cloud instance containing Java version data. This time, she explores some additional features offered between the application and database, such as custom queries and domain class projections.

HASHGNN: Deep-dive into Neo4j GDS’s new Node Embedding Algorithm

Philipp Brunenberg shows how the HashGNN algorithm implemented in the Graph Data Science Library generates embeddings for nodes in a graph. Node embedding algorithms are used to project nodes of a graph onto a lower dimensional embedding space.

CONFLUENT: Creating a Custom Connector in Confluent Cloud to Sink Data to Aura for Real-Time Analysis (Part 2)

Stu Moore demonstrates how to create a custom connector that can read JSON messages in a Confluent Cloud topic and create nodes and relationships for real-time graph analysis in Aura. Also, he performs testing and troubleshooting of common problems starting connectors.

SANDBOX: Build a Movie Database with Neo4j’s Knowledge Graph Sandbox

In this tutorial, B. Cameron Gain uses a Sandbox and Cypher to show the connections in a database of actors, movies and directors. He accompanies the explanations with queries and commands that can be copied and pasted directly into the command line.