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 in Neo4j - 22 April - Dmitry Vrublevsky from Neueda Labs

Dmitry Vrublevsky from Neueda Labs

This week’s featured community member is Dmitry Vrublevsky who works for Neueda Labs and has been very active in Neo4j’s community for quite some time.

He started helping people on StackOverflow and Slack and then started the development of the Neo4j plugin for all the Jetbrains IDEs. That work has evolved into a full featured database tool, which was recently featured on this blog.

Dmitry also spoke at the openCypher implementers meeting in February and will be at GraphConnect in London. He and his team is currently helping us to add some cool features to the Neo4j Browser.

Neo4j at the Galway-Mayo Institute of Technology


Multiple students from GMIT have been using Neo4j as part of their graph theory course and have been building a graph of the university timetable.

I wish I’d got to use Neo4j at university so I’m very jealous – it was Oracle all the way where I studied!

APOC, Call Data Records, GORM, Twitter Clone


Online Meetup: Building the Wikipedia Knowledge Graph


In this week’s Neo4j online meetup, Dr Jesús Barrasa and I showed how to load the Wikipedia Knowledge Graph into Neo4j and write queries against it.

We’ve been hosting meetups almost every week for the last couple of months so if you want to catch up on earlier episodes you can find all of them on the Neo4j Online Meetup playlist.

From The Knowledge Base


We also have a really cool discussion of ways to limit MATCHes in subqueries by Andrew Bowman, our featured community member in the 25 February 2017 edition of TWIN4j.

On GitHub: Mahout, Holocaust Research, Kafka Connector


There’s been an incredible amount of activity on GitHub this week. These were the most interesting projects that I came across.

    • UserLine automates the process of creating logon relations from MS Windows Security Events by showing a graphical realtion among users domains, source and destination logons as well as session duration.
    • Nigel Small created Memgraph – a Python library that provides a Neo4j-compatible in-memory graph store.
    • There were some updates to the European Holocaust Research Infrastructure project, which provides a business layer and JAX-RS resource classes for managing holocaust data.
    • Erick Peirson created cidoc-crm-neo4j which is a meta-implementation of the CIDOC Conceptual Reference Model (CRM). The CIDOC CRM provides definitions and formal structure for describing the implicit and explicit concepts and relationships used in cultural heritage documentation. The project uses Python’s neomodel to interact with a Neo4j database
    • gbrodar created pcap4j – a repository of scripts for analysing the output of the Unix pcap tool.
    • Mark Wood created neo4j-mahout which wraps calls to Mahout functions in Neo4j user defined functions. I played around with Mahout a couple of years ago so I’m quite excited to try combine it with Neo4j using this tool.
    • JunfengDuan created kafka-neo4j-connector, which transfers data from Kafka to Neo4j.

Neo4j Jobs


I’ve not listed jobs in TWIN4j before but I came across an interesting one posted by Musimap, a B2B cognitive music intelligence company in Brussels. They’re hiring a Full-Stack Web Developer with Neo4j and Python experience so if that sounds like your type of thing it might be worth applying.

If you have any jobs that you’d like me to feature in future versions, drop me a tweet @markhneedham.

Next Week


What’s happening next week in the world of graph databases?

Tweet of the Week


My favorite tweet this week was by Felix Victor Münch:

Don’t forget to retweet Felix’s post if you liked it as well!

That’s all for this week. Have a great weekend.

Cheers, Mark

 

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About the Author

Mark Needham, Developer Relations Engineer

Mark Needham Image

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.


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