# Kuzu — Embeddable Property Graph Database

> A high-performance embeddable graph database management system optimized for handling deeply recursive analytical queries on property graphs.

## Install

Save in your project root:

# Kuzu — Embeddable Property Graph Database

## Quick Use
```bash
pip install kuzu
```
```python
import kuzu
db = kuzu.Database("./mydb")
conn = kuzu.Connection(db)
conn.execute("CREATE NODE TABLE Person(name STRING, age INT64, PRIMARY KEY (name))")
conn.execute("CREATE REL TABLE Knows(FROM Person TO Person)")
conn.execute("CREATE (:Person {name: 'Alice', age: 30})")
conn.execute("CREATE (:Person {name: 'Bob', age: 25})")
conn.execute("MATCH (a:Person)-[:Knows]->(b:Person) RETURN a.name, b.name")
```

## Introduction
Kuzu is an embedded graph database built from the ground up for high-performance analytical queries on property graphs. Developed by researchers at the University of Waterloo, it uses columnar storage and vectorized execution to deliver fast multi-hop traversals and pattern matching while running as a library inside your application with no separate server process.

## What Kuzu Does
- Stores and queries property graphs with node and relationship tables using Cypher
- Executes multi-hop recursive path queries efficiently with worst-case optimal join algorithms
- Provides an embeddable library for Python, Node.js, Rust, Java, and C/C++
- Supports structured property types including lists, maps, structs, and unions
- Imports data from CSV, Parquet, NumPy, Pandas, and Arrow sources

## Architecture Overview
Kuzu uses a columnar storage layout optimized for graph workloads. The query processor implements factorized query execution and worst-case optimal join algorithms that avoid the intermediate result blowup common in traditional graph databases. A buffer manager and disk-based storage allow Kuzu to handle graphs larger than memory. The system compiles Cypher queries into vectorized physical plans for efficient CPU utilization.

## Self-Hosting & Configuration
- Install via pip, npm, cargo, or Maven depending on your language
- Create a database by pointing to a directory path; files are managed automatically
- Import large graphs using the COPY FROM command with CSV or Parquet files
- Configure buffer pool size with the buffer_pool_size parameter for memory management
- Use the CLI shell (kuzu_shell) for interactive exploration and schema management

## Key Features
- Cypher query language is familiar to users of Neo4j and other graph databases
- Worst-case optimal joins prevent performance cliffs on complex graph patterns
- Columnar and vectorized execution brings analytical database speed to graph queries
- Structured schema with typed node and relationship tables ensures data integrity
- Zero-copy integration with Apache Arrow and Pandas for data science workflows

## Comparison with Similar Tools
- **Neo4j** — Neo4j is a client-server graph database; Kuzu is embeddable with columnar analytical performance
- **DuckDB** — DuckDB is an analytical SQL database; Kuzu is purpose-built for graph pattern matching and recursive queries
- **CozoDB** — CozoDB uses Datalog; Kuzu uses Cypher and worst-case optimal joins for graph-specific optimization
- **SQLite** — SQLite is a relational database; Kuzu handles graph traversals that would require complex recursive CTEs in SQL
- **Amazon Neptune** — Neptune is a managed cloud graph service; Kuzu is a free embeddable library with no infrastructure cost

## FAQ
**Q: Does Kuzu use Cypher or a custom query language?**
A: Kuzu uses the openCypher query language, the same language used by Neo4j, so existing Cypher knowledge transfers directly.

**Q: Can Kuzu handle graphs that don't fit in memory?**
A: Yes. Kuzu uses disk-based storage with a buffer manager, so it can process graphs larger than available RAM.

**Q: Is Kuzu suitable for transactional workloads?**
A: Kuzu supports ACID transactions, but it is optimized for analytical graph queries. For high-throughput OLTP, a server-based graph database may be more appropriate.

**Q: Can I use Kuzu with GraphRAG or knowledge graph applications?**
A: Yes. Kuzu is well-suited for knowledge graph storage and retrieval, and integrates with LangChain and LlamaIndex for RAG pipelines.

## Sources
- https://github.com/kuzudb/kuzu
- https://kuzudb.com

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Source: https://tokrepo.com/en/workflows/asset-15f5a660
Author: AI Open Source