Datalevin: The Definitive Guide to Logical and Intelligent Databases

Move beyond SQL’s table-first model and build applications around durable, connected facts.

Modern application state rarely fits neatly into rows and joins. It includes transactions, graph relationships, documents, full-text search, vector similarity, and persistent memory for AI systems. Assembling these capabilities with SQL strings, ORM layers, extensions, and sidecar services creates complexity at every boundary.

Datalevin: The Definitive Guide to Logical and Intelligent Databases presents a coherent alternative. Datalevin is a compact, open-source database that combines ACID transactions and durable LMDB-backed storage with a fact-first data model and composable Datalog queries. Relational records, graph edges, documents, search hits, vector neighbors, and agent memory become different views over one logical database.

Through practical explanations and examples, you will learn how to:

Model evolving application state as entities, attributes, and durable facts Write Datalog queries, rules, recursion, transactions, and pull patterns Replace SQL and ORM glue with composable queries represented as data Design relational, graph, and document models that evolve cleanly Combine full-text search, vector similarity, embeddings, and logical constraints Tune storage, analyze query plans, ingest data efficiently, and operate Datalevin in production Build persistent agent memory with scoped recall, context assembly, provenance, and truth maintenance
Who This Book Is For

This guide is for engineers building embedded applications, backend services, knowledge graphs, search-intensive products, durable workflows, or AI systems that need reliable long-term state. Basic database literacy is helpful, but no prior Datalog experience is required.

Written by Datalevin’s creator and maintainer, this book shows how to make a logical database the durable center of modern application state: one place to store facts, traverse relationships, derive knowledge, preserve evidence, and give intelligent systems memory.