Books

We'll start with nodes, relationships and Cypher, as it'll make everything else easier later on. Then, we design a schema, chunk documents, extract entities and add embeddings. Then, we'll mix vectors with structure, run graph algorithms, think about rules and ontologies, and connect AI agents through safe, traceable tools. We'll also keep the graph fresh, measured and recoverable, because if it's stale, users won't trust it.

What if you could build a graph database the way SQLite is built to disappear into an application? This book takes you inside the engine, from storage pages and transactions to traversal, queries and crash recovery. With complete working code, you’ll build a fast, durable embedded graph database from the ground up.