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Graph Databases by Ian Robison, Jim Webber & Emil Eifrem

This is a book aims at practicality, focus on managing and querying highly connected data using schema-free graph models.

The book is authored by engineers at Neo4J.

Key takeaways:

  • Graph databases excel at highly connected data where relational databases and aggregate NoSQL stores struggle: Query patterns that require traversing various records via links.
  • Graph databases are more adept at querying graph-like properties, like all transitive friends of a person, where relational joins degrade exponentially with depth. Graph traversal stays constant (O(1) per hop with index-free adjacency).
  • The property graph model (nodes + relationships, both with key-value properties) is simple yet covers the vast majority of use cases.
  • Graph databases are schema-free and additive: New node types and relationships can be added without breaking existing queries.

The book covers the followings:

  • The Cypher query language.
  • The property graph data model.
  • Best practices/commons pitfalls and architectural patterns when working with graph databases.
  • How to design data with the graph data model?

A Little of History

At around 1999, the founders of Neo4j were struggling with an enterprise content management system where 50% of their engineering effort was spent “fighting” relational databases. While SQL handled discrete data well, it was extremely slow and complex for managing connected data, which represents most of their use cases.

Failing to find an existing solution on the web (using “Altavista”, an antique search engine), the team built a native graph database from scratch. Their goal was to combine the reliability of relational databases (ACID transactions) with a graph-centric model for the 21st century (?).

Since then, graph databases are now mission-critical in logistics (routing), finance (entitlements), airlines, and healthcare.

Basically, the philosophy is to embrace “graph thinking” to empower data connectivity, which allows unlocking insights that traditional databases cannot.