Cozo – new Graph DB with Datalog, embedded like SQLite
Hi HN, I have been making this Cozo database since half a year ago, and now it is ready for public release. My initial motivation is that I want a graph database. Lightweight and easy to use, like SQLite. Powerful and performant, like Postgres. I found none of the existing solutions good enough. Deciding to roll my own, I need to choose a query language. I am familiar with Cypher but consider it not much of an improvement over CTE in SQL (Cypher is sometimes notationally more convenient, but not more expressive). I like Gremlin but would prefer something more declarative. Experimentations…
In plain words
Cozo is an embedded graph database designed to be lightweight and accessible like SQLite while offering the power and performance of Postgres. It uses Datalog as its query language, which the creator found more expressive and declarative than alternatives like Cypher or Gremlin. The database targets developers seeking a practical graph database solution without the constraints of property graph models or performance limitations of triple stores.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, I have been making this Cozo database since half a year ago, and now it is ready for public release. My initial motivation is that I want a graph database. Lightweight and easy to use, like SQLite. Powerful and performant, like Postgres. I found none of the existing solutions good enough. Deciding to roll my own, I need to choose a query language. I am familiar with Cypher but consider it not much of an improvement over CTE in SQL (Cypher is sometimes notationally more convenient, but not more expressive). I like Gremlin but would prefer something more declarative. Experimentations with Datomic and its clones convinced me that Datalog is the way to go. Then I need a data model. I find the property graph model (Neo4j, etc.) over-constraining, and the triple store model (Datomic, etc.) suffering from inherent performance problems. They also lack the most important property of the relational model: being an algebra. Non-algebraic models are not very composable: you may store data as property graphs or triples, but when you do a query, you always get back relations. So I decided to have relational algebra as the data model. The end result, I now present to you. Let me know what you think, good or bad, and I'll do my best to address them. This is the first time that I use Rust in a significant project, and I love the experience!
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