This Week in Neo4j: New Release of Neo4j 5, ETL Best Practices, NestJS Node App, Feature Engineering, Graph Embeddings, and More


We released Neo4j 5 this week! It’s the next-generation, foundational database behind Neo4j Graph Database, Neo4j Community Edition, Neo4j Graph Data Science, AuraDB, and AuraDS.

For developers, it offers better, easier ways to write queries with more expressive Cypher syntax. The performance advantage over relational databases is extended through K-Hop query optimization and new and enhanced indexes. The Community Edition gets an upgraded runtime which accelerates queries by 30 percent. Support for Panda dataframes in the Python driver allows exported Neo4j result sets to integrate into common workflows for data scientists. There are many more new features like Autonomous Clustering and Fabric to scale out and deal with high throughput and very large graphs more efficiently.

You can learn all about Neo4j 5 during NODES 2022 next week in the following sessions:

  • What’s New in Aura and Neo4j 5 for Developers
  • Introduction to Neo4j 5 for Administrators
  • Neo4j 5 Foundations for Scale
  • Graph Pattern Matching
  • Neo4j Ops Manager, Intro and Roadmap
  • Index Changes in Neo4j 5

Register for free NODES 2022!

Cheers,
Yolande Poirier

P.S. Don’t forget to enter our contest for a chance to win $500 by inviting your friends to NODES! Ask your network to use the registration link with your full name to enter. Create your link here.
 

In his NODES 2022 presentation, Rhys explains why the Financial Times turned to graph technologies – Neo4j and GraphQL – to build a user-friendly picture of multiple AWS accounts.

Rhys Evans is a principal engineer at the Financial Times, one of the world’s fastest media sites. After almost a decade as a front-end developer, he’s gradually turned to the dark side, spending most of his time building, optimizing, and – if he’s lucky – switching off bits of the Node.js stack. You can follow him on Twitter.


 
DATA MANAGEMENT: Graph ETL and Neo4j ETL Best Practices
What’s the best way to ingest and transform data for graph databases? Well, it depends… In this article, David Hughes, Principal Graph Consultant at Graphable, briefly surveys various methods and then focuses on using the graph insights platform GraphAware Hume for loading data into a graph database.
 
SUSTAINGRAPH: A Knowledge Graph for Tracking Sustainable Development Goals
The case study described in the article focuses on greening the Athens metropolitan area and tackling the impact of heat waves in the area of Attica in Greece.
 
GRAPH EMBEDDINGS: How to Solve Bigger Problems at Scale
In this blog, Scott M. Fulton interviews graph expert Tomaz Bratanic and others to explain how graph embedding’s dimensionality reduction enables lower-dimensional representations to retain meaningful properties of the original data.
 
WORKSHOP: Handling Neo4j Data With Apache Hop

This video is a hands-on crash course in Neo4j. Matt Casters introduces you to Apache Hop, the orchestration platform for all aspects of data and metadata orchestration. He goes over the settings and basic features, as well as Neo4j functionality with Apache Hop. Enjoy!


GRAPH: Feature Engineering With Neo4j and Amazon SageMaker

In this post, Ben Lackey and Antony Prasad Thevaraj explore how graph features engineered in Neo4j can be used in a supervised learning model trained with Amazon SageMaker.

API: Creating API in NestJS With @graphql/neo4j and AWS Cognito

In this blog, akkonrad creates a Node application with NestJS and uses the Neo4j graphql module to interact with the database. He secures the app with AWS Cognito.

NODES 2022: Anyone Can Learn Graph: Dr. Kateryna Nesvit

In this interview, Dr. Kateryna Nesvit, VP of Data Science for a major IT firm, shares her professional journey, and how graph databases served as one platform for her many accomplishments. She is presenting the talk “Discover Invisible Patterns in Your Data” at NODES 2022.

TWEET OF THE WEEK: @Eva_Klijn

Don’t forget to retweet if you like it!
 

… Of Special Interest
    •  18MB of football data from Transfermarkt, 6 CSV files, 1.1M nodes including 800 clubs, 58k games and almost 50k players mapped and imported into Neo4j in 10 minutes without writing a single line of code. You can check out the Data Importer.
    • Come see us at AWS re:Invent! We’ll be in Vegas from November 28 – December 2 hosting a booth and holding a session about Neo4j and Amazon SageMaker. Join us!
    • Cypherhound is a Python app that contains 190+ Neo4j Cyphers for BloodHound data Check it out!
    • Will Lyon shares the video from his NACIS 2022 talk – “Making Sense of Geospatial Data With Knowledge Graphs and Neo4j.” Watch it now.