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 have a tutorial of the Neo4j ETL Tool, a React.js application that uses the new temporal and geospatial data types, a new release of the JDBC Driver, and more!
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Featured Community Member: David Meza
This week’s featured community member is David Meza, Chief Knowledge Architect at NASA.
David Meza – This Week’s Featured Community Member
David has been part of the Neo4j community for several years and is best known for his work building a graph of the public NASA Engineering Network lesson learned database, which he wrote about in July 2015. He was also interviewed about his work on the Graphistania podcast.
David’s How NASA Finds Critical Data Through a Knowledge Graph talk at GraphConnect San Francisco 2016 was one of the most popular at the conference. You can also find the slides from David’s talk.
On behalf of the Neo4j community, thanks for all your work David!
Tap into Hidden Connections – Translating Your Relational Data to Graph
Jennifer starts by showing how to enable the tool via an activation key , and then imports the Northwind dataset from a PostgreSQL relational database into Neo4j.
If you’d like to get an activation key send us an email firstname.lastname@example.org and we’ll send one over.
Neo4j Date And Spatial Types: Yelp and React.js, Open Beer Database
Will Lyon wrote a blog post in which he shows how to build an application that makes use of the temporal and geospatial data types that were introduced in Neo4j 3.4.
Will takes us through the steps to build a React.js dashboard type application that allows a user to search for businesses by location that have reviews within a certain date range and display some charts based on aggregations of these reviews.
An intro to graph databases
If you’re just getting into graph databases this is an excellent overview of the field and different tools available.
Aaron Lelevier has been learning about Graph Theory and has written a blog post in which he distills his learnings.
Aaron explains the different types of graphs, ways of representing them, and shares a project where he built a bidirectional graph of his GitHub followers.
Neo4j Enterprise on AWS, CLEVR graph, Security Engineering Tools
- David Mack released CLEVR graph – a dataset that aims to help further research into machine reasoning on graph datasets. It contains a set of questions and answers about transport network graphs.
- Neo4j Enterprise is now available on the AWS Marketplace. Give it a try and let us know how you get on – email@example.com
- I recently came across Amass – a subdomain enumeration tool that performs network mapping and Open-source intelligence gathering by using Neo4j and Vis.js for visualization.
- redmed666 created Mal6raph – a framework which can be used to compare samples between them from a code perspective as part of malware analysis. It allows you to upload samples analysed by radare, display those samples, and display similar ones based on function analysis.
The Sinar Project: The making of a network chart
A couple of years ago there was a big story about the 1Malaysia Development Berhad (IMDB), a fund that was created by the Malaysian government to promote economic development through global partnerships and foreign direct investment. The FBI posted a filing to seize their assets under the US Department of Justice and FBI’s Kleptocracy Asset Recovery Initiative.
There was an article written back in 2016 by The Sinar Project where they explained how they’d used their Popit Database of Politically Exposed Persons helps uncover culprits and hold officials accountable.
This week sweemeng, a member of the Sinar Project, wrote a blog post explaining in more detail how they built the graph, how the data’s organised, and why their method worked for exploring this type of data.
You can find the source code for the data loader in the sinar/popit_relationship GitHub repository.
Neo4j JDBC Driver 3.3.1 Release Is Here
This week our friends at LARUS released version 3.3.1 of the Neo4j-JDBC driver.
The release has been upgraded to work with recent Neo4j 3.3.x versions and Bolt driver 1.4.6. Work is in progress on Neo4j 3.4.x and drivers 1.6.x.
The main addition has been support for Neo4j clusters, the JDBC driver now supports, routing, read-only transaction, routing-policies and bookmarks for causal consistency.
There are also other improvements including support for in-memory databases, a debug feature to inspect how the driver works when used by third-party tools, and support for TrustStrategy.
If you want to use the Neo4j-JDBC driver in your application, you can depend on
org.neo4j:neo4j-jdcb:3.3.1 in your build setup or grab the latest release from GitHub.
What’s happening next week in the world of graph databases?
June 18th 2018
June 21st 2018
June 21st 2018
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.
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