Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days.
This week we learn how to supercharge developer productivity with the latest release of neo4j-graphql.js, there’s a new release of the Kettle plugins for Neo4j, we have a GraphConnect experience report, and blog posts showing how to use the new Jaccard and Cosine Similarity algorithms.
Featured Community Member: Ralf Becher
This week’s featured community member is Ralf Becher, Managing Director at TIQ Solutions GmbH.
Ralf Becher – This Week’s Featured Community Member
Ralf has been a member of the Neo4j community for more than 6 years and has built integrations with the Tableau and QlikView business intelligence products, as well as presenting at many meetups on this subject.
Ralf was also interviewed on the Graphistania podcast in April 2015, where he explained how the combination of graphs and BI tools can help us gain even more insight into our data.
On behalf of the Neo4j community, thanks for all your work Ralf!
Announcing New Features In neo4j-graphql.js
Will Lyon announced a new version of neo4j-graphql.js, which now makes it possible to spin up a GraphQL API backed by a graph database with just type definitions.
The 1.0.1 release has several new features to help supercharge your developer productivity. These include:
- Auto-generate Query/Mutation types and resolvers
- Augment a GraphQL schema with pagination, ordering, and _id fields
- Flexible handling of relationship types, including relationship properties
- Middleware support can be used to implement authentication/authorization with generated resolvers
If you haven’t tried out GraphQL with Neo4j, now is the time!
Creating a Neo4j Sandbox
The Neo4j Sandbox creates a temporary Neo4j instance in the cloud for learning about Neo4j graphs. We have several sandboxes with built in datasets such as the Panama Papers and Russian Twitter Trolls, but you can also create a blank sandbox if you just want to play with Neo4j and aren’t able to install the Neo4j Desktop.
Cosine similarity on GoT, Finding your neighbours, Jaccard similarity on product categories
- Tomaz Bratanic has written a blog post in which he shows how to build a similarity graph of product categories using Jaccard similarity algorithm, and then find communities amongst those categories using the Label Propagation algorithm.
- I’ve written a blog post showing how to use the Cosine similarity algorithm to find similar Game of Thrones episodes based on the characters that appear in each episode.
- Max De Marzi has written a blog post in which he shows how to write a stored procedure to efficiently find a node’s neighbors. Max’s approach will soon be added to the APOC library.
Releases: Kettle plugins for Neo4j
Matt Casters released a new version of the Kettle plugins for Neo4j. This version adds Metadata Injection support to handle more complex scenarios.
For those that want to test WebSpoon, you can use a Docker image that Matt created with all the latest plugins installed. To run the latest Neo4j server alongside to test it, Matt has also created a Docker Compose file which you can find in the dockerfile-webspoon-neo4j GitHub repository.
GraphConnect Experience Report, Word-Pair Frequency Graph, Medium Graph
- Mos Zhang has written up an experience report from the GraphConnect conference that was hosted in New York a couple of weeks ago.
- Devansh Trivedi has been participating in the 100 days of Machine Learning challenge, and on Day 1 built a Word-Pair Frequency Graph in Neo4j. Good luck with the rest of the challenge Devansh!
- Sahil Jadon has written a blog post showing how you might build a graph based on the Medium blogging platform. Sahil then shows how to write recommendation queries to suggest new content for users to read.
On the podcast: Michael McKenzie
This week Rik interviewed Michael McKenzie on the Graphistania podcast. Michael was our featured community member of the week for 4th August 2018.
Michael explains how he first became interested in graphs while trying to work out how building codes and texts were interrelated – an information graph being the solution to this problem.
Michael goes on to explain his experience working with the Cypher query language and his use of the GRANDstack on some personal passion projects.
What’s happening next week in the world of graph databases?
October 11th 2018
Tweet of the Week
My favourite tweet this week was by Lilach Manheim:
Don’t forget to RT if you liked it too.
That’s all for this week. Have a great weekend!
About the Author
Mark Needham , Developer Relations Engineer
Mark Needham is a graph advocate and developer relations engineer at Neo4j.
As a developer relations engineer, Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team, helping to build the Causal Clustering feature released in Neo4j 3.1. Mark writes about his experiences of being a graphista on a popular blog at markhneedham.com. He tweets at @markhneedham.