Kuzu V0 136 Official

pip install kuzu==0.136.0

While v0.136 is an incremental release, several pragmatic changes make day-to-day work noticeably smoother:

By [Your Name/Technical Writer]

The landscape of graph databases is shifting. For years, the industry was dominated by massive, server-centric architectures designed for enterprise-scale silos. However, the rise of local-first software, edge computing, and AI applications running on developer machines has created a demand for speed, portability, and simplicity.

Enter Kuzu, the highly scalable, open-source embeddable graph database built for the modern data stack. With the release of Kuzu v0.136, the project takes another significant step forward, refining its query processing engine and expanding its ecosystem support. This release focuses on performance stability, extended language bindings, and the tools necessary to bridge the gap between relational data and graph structures. kuzu v0 136

Here is a deep dive into what makes Kuzu v0.136 a critical update for developers working with complex, connected data.

If you are currently on a previous version (e.g., v0.120 or v0.130), note the following breaking changes:

Function renaming: The size() function for lists is now list_length() (aligned with Cypher standard).

Explicit COMMIT: Auto-commit on connection close is disabled. You must now call conn.commit() after a write transaction.

A migration script is available in the official documentation: /kuzu/v0.136/upgrade_guide.md pip install kuzu==0

result = conn.execute("MATCH (a:Person) RETURN a.name, [ (a)-[:Knows]->(b) | b.name ] AS knows_list") print(result.get_as_data_frame())

conn.execute("CREATE NODE TABLE Person(id INT64, name STRING, PRIMARY KEY(id))") conn.execute("CREATE REL TABLE Knows(FROM Person TO Person, since DATE)")

Getting started with Kuzu has never been easier. The v0.136 package is available on PyPI and major package managers. While v0

For a Python developer, the workflow is seamless:

import kuzu
Kuzu uses a morsel-driven, vectorized query processor. In v0.1.36, the team focused on specific optimization rules: