When Your Data Is Not a Graph

I often get asked at the Neo4j trainings and meetups about which types of data or use cases a graph database doesn’t handle. While graph data structure models the world we live in exceptionally well there are some use cases and scenarios where your data is not a graph – or more likely not ONLY a graph.Read more….

Getting Acquainted with an Unknown Graph

Finding your way around an unknown graph can seem a bit ambiguous at first due to Neo4j being schema-free. Especially if you’re newer to graph databases and used to a relational database where you would simply open the ERD and have a look through the tables. Just because Neo4j is schema-free doesn’t mean that schema-like elements are not present. The Neo4j graph database schema elements are composed of Label Names, Relationship Types, Indexes and Constraints on Property Keys. Let’s look at some techniques for getting aquatinted with an unknown graph.Read more….

Graph Advantage: Building a Smarter Data Lake

Organizations today are amassing data at faster rate than ever before into their data lakes and often that data lake is where that data remains. Enterprises are looking for effective ways to utilize the huge volumes and varying data they’ve been collecting in their data lakes in order to respond to competitive pressures, regulations and provide empirical business guidance. It’s time to build a smarter data lake and let your data drive your organization forward.Read more….

Graph Advantage: Identity and Access Management

Identity and Access Management for a complex media workflow was actually my first experience with Neo4j as a graph database solution that enabled us to represent access throughout the flow in a structure realistic to the way it actually existed. During the last 4+ years since then I’ve continued tosee Identity and Access Management as major beneficiary of the flexible data model and performance of non-JOIN node traversal of the Neo4j graph database.Read more….

Relationship Direction in Cypher is Important

The relationship direction between two nodes is required for Cypher write queries, but can be ignored on Cypher read queries. Cypher is a graph database declarative and textual query language by Neo4j, which supported by a larger group as OpenCypher to make Cypher the SQL for graph databases. Cypher looks a bit like ASCII art in it’s representation of graph-related traversal patterns, which makes it quite intuitive and fun to use in querying graphs.Read more….

systemd Neo4j service on Ubuntu

systemd ships as the default process manager on Ubuntu 15.04; get the neo4j systemd service file to install and learn about the configuration. systemd has a lot of great features and I encourage you to check it out as it’s a big improvement IMO from SystemV and Upstart. If you’ve started working with systemd to manage your neo4j process, then youRead more….

Understanding DETACH DELETE in Cypher

DETACH DELETE in Cypher is an example of why Cypher is one of my favorite ways of interacting with the Neo4j graph database. The declarative graph query language is constantly evolving to ease the requirements of querying Neo4j. This benefit in ease of interaction, however, can often further remove the query writer from needing to understand the inner Read More......