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Check out Part 2 of Ebru Cucen and Fahran Wallace's blog series, in which they discuss their experience ingesting 400 million nodes and a billion relationships into Neo4j and what they discovered along the way.

As data becomes ubiquitous and deeply interconnected, tracing where who or which system that data comes from - its lineage - will create bigger problems and opportunities for us on the horizon. Watch the recording of James Bowkett talk from NODES 2022 - Neo4j Online Developer Education Summit 202 on 'Tracing Your Data's DNA.'

Fahran Wallace and Ebru Cucen's most recent blog post is part 1 of a three-part series. They investigate how OpenCredo ingested 400 million nodes with a billion relationships into Neo4j.

Neo4j in Action is a comprehensive guide to designing, implementing, and querying graph data using Neo4j.

With Cypher approaching feature completeness, improvements to performance would allow Cypher to become the first entry point to interact with Neo4j

t's been more than a year now since I rolled out Neo4j Graph Database Server image in Amazon EC2. Neo4j graph database server images per AWS region

Let's remind ourselves with the data set we are using: Neo4j Super nodes: 5 nodes representing cities/towns (for example “London”, “Manchester”, “Edinburgh”

Neo4j Supernode represents nodes with dense relationships (100K or more), which are quickly becoming bottlenecks in graph traversal algorithms when using Neo4J.