Kùzu

Kùzu is an in-process property graph database management system (GDBMS) built for query speed and scalability. Kùzu is optimized for handling complex join-heavy analytical workloads on very large graph databases, with the following core feature set:

Flexible Property Graph Data Model and Cypher query language
Embeddable, serverless integration into applications
Columnar disk-based storage
Columnar sparse row-based (CSR) adjacency list/join indices
Vectorized and factorized query processor
Novel and very fast join algorithms
Multi-core query parallelism
Serializable ACID transactions

Kùzu is being actively developed at University of Waterloo as a feature-rich and usable GDBMS. Kùzu is available under a permissible license. So try it out and help us make it better! We welcome your feedback and feature requests.

Build

To build from source code, Kùzu requires Cmake(>=3.11), Python 3, and a compiler that supports C++20.

Perform a full clean build without tests and benchmark:
- make clean && make release
Perform a full clean build with tests and benchmark (optional):
- make clean && make all
Run tests (optional):
- make test

For development, use make debug to build a non-optimized debug version. To build in parallel, pass NUM_THREADS as parameter, e.g., make NUM_THREADS=8.

After build, our CLI binary kuzu_shell is available under the directory build/release/tools/shell/.

Installation

Precompiled binary

Precompiled binary of our latest release can be downloaded here.

Python package

Our Python package can be directly install through pip.

pip install kuzu

For more installation and usage instructions, please refer to our website.

Example

We take tinysnb as an example graph, which is under dataset/tinysnb in our source code, and can be downloaded here.

CLI

Start CLI

./build/release/tools/shell/kuzu_shell -i "./test.db"

Schema Definition

kuzu> CREATE NODE TABLE person (ID INt64, fName STRING, gender INT64, isStudent BOOLEAN, isWorker BOOLEAN, age INT64, eyeSight DOUBLE, birthdate DATE, registerTime TIMESTAMP, lastJobDuration interval, workedHours INT64[], usedNames STRING[], courseScoresPerTerm INT64[][], PRIMARY KEY (ID));
kuzu> CREATE REL TABLE knows (FROM person TO person, date DATE, meetTime TIMESTAMP, validInterval INTERVAL, comments STRING[], MANY_MANY);

Data Import

kuzu> COPY person FROM "dataset/tinysnb/vPerson.csv" (HEADER=true);
kuzu> COPY knows FROM "dataset/tinysnb/eKnows.csv";

After creating node/rel tables, and importing csv files, you can now run queries!

kuzu> MATCH (b:person)<-[e1:knows]-(a:person)-[e2:knows]->(c:person) RETURN COUNT(*);

Python

import kuzu

db = kuzu.database('./testpy')
conn = kuzu.connection(db)
conn.execute("CREATE NODE TABLE person (ID INt64, fName STRING, gender INT64, isStudent BOOLEAN, isWorker BOOLEAN, age INT64, eyeSight DOUBLE, birthdate DATE, registerTime TIMESTAMP, lastJobDuration interval, workedHours INT64[], usedNames STRING[], courseScoresPerTerm INT64[][], PRIMARY KEY (ID));")
conn.execute("CREATE REL TABLE knows (FROM person TO person, date DATE, meetTime TIMESTAMP, validInterval INTERVAL, comments STRING[], MANY_MANY);")
conn.execute("COPY person FROM 'dataset/tinysnb/vPerson.csv' (HEADER=true);")
conn.execute("COPY knows FROM 'dataset/tinysnb/eKnows.csv';")
result = conn.execute("MATCH (b:person)<-[e1:knows]-(a:person)-[e2:knows]->(c:person) RETURN COUNT(*)")
while result.hasNext():
  print(result.getNext())

Refer to our Data Import and Cypher section for more information.

Code of Conduct

We are developing Kùzu in a publicly open GitHub repo and encourage everyone to comment and discuss topics related to Kùzu. However, we ask everyone to be very respectful and polite in discussions and avoid any hurtful language in any form. Kùzu is being developed in Canada, a land that is proud in their high standards for politeness and where a person you bumped into on the road will likely apologize to you even if it was your fault: so please be kind and respectful to everyone. If you prefer not to discuss something through open issues and discussions, you can always reach us through email.

Citing Kùzu

If you are a researcher and use Kùzu in your work, we encourage you to cite our work. You can use the following BibTeX citation:

@inproceedings{kuzu:cidr,
  author =  {Xiyang Feng and
             Guodong Jin and
             Ziyi Chen and
             Chang Liu and
             Semih Saliho\u{g}lu},
  title={K\`uzu Graph Database Management System},
  booktitle={CIDR},
  year={2023}
}
@misc{kuzu-github,
  author =  {Xiyang Feng and
             Guodong Jin and
             Ziyi Chen and
             Chang Liu and
             Semih Saliho\u{g}lu},
  title = {{K\`uzu Database Management System Source Code}},
  howpublished = {\url{https://github.com/kuzudb/kuzu}},
  month        = nov,
  year         = 2022
}

Contact Us

You can contact us at contact@kuzudb.com or join our Slack workspace.

MattAlp/kuzu