Resources

Videos, Slides, Case Studies and other GraphAware related resources

Spring Data Neo4j: Graph Power Your Enterprise Apps

21 Nov 2017 slides Neo4j graphs applications

A few weeks ago Spring Data Neo4j version 5 was released as part of the Spring Data 2.0 release train. Time to present the Spring way to work with Neo4j and introduce the latest features SDN 5 and its supporting library Neo4j-OGM 3 provide. The talk will also give an overview of the overall architecture and shows examples how to build modern, compact back-ends and web-applications using Spring Data Neo4j. Of course we will give a glance of what the future will bring to Spring Data Neo4j.

Neo4j Online Meetup #30: Spring Data Neo4j 5 and OGM3

19 Nov 2017 videos

SDN is a Spring Data project for Neo4j. It uses Neo4j-OGM under the hood (very much like Spring Data JPA uses JPA) and provides functionality known from the Spring Data world like repositories, derived finders or auditing. Neo4j recently released Spring Data 2.0 (Kay) / Spring Data Neo4j 5.0 and in this session we’ll show some of the new cool features. This release contains support for dynamic properties, schema based loading, field access only, and more.

Graph Database Prototyping made easy with Graphgen

19 Nov 2017 slides graph databases

Graphgen aims at helping people prototyping a graph database, by providing a visual tool that ease the generation of nodes and relationships with a Cypher DSL. Many people struggle with not only creating a good graph model of their domain but also with creating sensible example data to test hypotheses or use-cases. Graphgen aims at helping people with no time but a good enough understanding of their domain model, by providing a visual dsl for data model generation which borrows heavily on Neo4j Cypher graph query language. The ascii art allows even non-technical users to write and read model descriptions/configurations as concise as plain english but formal enough to be parseable. The underlying generator combines the DSL inputs (structure, cardinalities and amount-ranges) and combines them with a comprehensive fake data generation library to create real-world-like datasets of medium/arbitrary size and complexity. Users can create their own models combining the basic building blocks of the dsl and share their data-descriptions with others with a simple link.

Knowledge Graph Search with Elasticsearch — Luanne Misquitta and Alessandro Negro, GraphAware

16 Nov 2017 videos

In this talk, Luanne will share insights about the business value of knowledge graphs and their contribution to relevant search in an e-commerce domain for a Neo4j customer. With text search and catalog navigation being the entry point of users to the system and in fact, driving revenue, the talk will explain the challenges of relevant search and how graph models address them. Dr. Alessandro will then talk about various techniques used for information extraction and graph modelling. He will also demonstrate how to seamlessly introduce knowledge graphs into an existing infrastructure and integrate with other tools such as ElasticSearch, Kafka, Apache Spark, OpenNLP and Stanford NLP.