# CozoDB — Hybrid Relational-Graph-Vector Database with Datalog

> A transactional database that unifies relational, graph, and vector search queries in a single Datalog-based query language.

## Install

Save as a script file and run:

# CozoDB — Hybrid Relational-Graph-Vector Database with Datalog

## Quick Use
```bash
pip install pycozo
```
```python
from pycozo import Client
db = Client()
db.run("?[name, age] <- [['Alice', 30], ['Bob', 25]]")
db.run(":create people {name: String => age: Int}")
db.run("?[name, age] <- [['Alice', 30]] :put people {name => age}")
db.run("?[name, age] := *people{name, age}, age > 27")
```

## Introduction
CozoDB is an embedded database that combines relational tables, graph traversal, and vector similarity search under a single Datalog-based query language called CozoScript. It was designed for applications that need to query across structured, connected, and embedding data in one unified interface, without stitching together separate databases.

## What CozoDB Does
- Stores relational data in tables with typed schemas and ACID transactions
- Supports recursive graph traversal queries via Datalog fixed-point evaluation
- Provides built-in HNSW vector indexes for approximate nearest-neighbor search
- Runs as an embedded library in Rust, Python, JavaScript, Java, or as a standalone server
- Allows time-travel queries to read historical data at any past transaction point

## Architecture Overview
CozoDB uses a storage engine abstraction that supports multiple backends: SQLite for embedded use, RocksDB for high-throughput workloads, and an in-memory engine for testing. The query engine compiles CozoScript into a Datalog evaluation plan with magic-set optimization. Graph queries use semi-naive evaluation for efficient fixed-point computation, and vector indexes are maintained as special stored relations alongside regular tables.

## Self-Hosting & Configuration
- Install the Python client with pip, or add the Rust crate as a Cargo dependency
- Choose a storage backend (SQLite, RocksDB, or memory) when creating the database
- Run as a standalone HTTP server for language-agnostic access via REST API
- Create HNSW vector indexes on relations to enable similarity search
- Configure index parameters like ef_construction and M for vector search tuning

## Key Features
- Datalog query language naturally expresses recursive graph patterns and joins
- HNSW vector indexes are first-class citizens alongside relational tables
- Time-travel queries access any historical database state by transaction ID
- Multiple storage backends let you choose between portability and performance
- Embeddable in Rust, Python, Node.js, Java, Swift, and Go with native bindings

## Comparison with Similar Tools
- **Neo4j** — Neo4j is a server-based graph database; CozoDB combines graph, relational, and vector in one embeddable engine
- **DuckDB** — DuckDB is an analytical SQL engine; CozoDB uses Datalog for recursive and graph queries
- **Milvus** — Milvus is a dedicated vector database; CozoDB integrates vector search with relational and graph queries
- **SQLite** — SQLite is a relational database; CozoDB adds graph traversal and vector search on top of SQLite as a backend
- **Dgraph** — Dgraph uses GraphQL; CozoDB uses Datalog which supports recursive queries natively

## FAQ
**Q: What is CozoScript?**
A: CozoScript is CozoDB's query language based on Datalog. It supports relational queries, recursive graph traversal, aggregation, and vector search in a unified syntax.

**Q: Can CozoDB replace a traditional SQL database?**
A: For embedded use cases, yes. CozoDB handles relational workloads and adds graph and vector capabilities. For large-scale OLTP, a dedicated SQL database may be more appropriate.

**Q: Does CozoDB support concurrent access?**
A: Yes. CozoDB supports concurrent readers with serializable write transactions. The RocksDB backend provides the best concurrency performance.

**Q: Is CozoDB suitable for AI/RAG applications?**
A: Yes. The built-in HNSW vector indexes make CozoDB a good fit for retrieval-augmented generation pipelines that also need structured and graph queries.

## Sources
- https://github.com/cozodb/cozo
- https://docs.cozodb.org

---
Source: https://tokrepo.com/en/workflows/asset-01510f17
Author: Script Depot