Announcing GQLAlchemy 1.1

GQLAlchemy 1.1 introduces several new features to enhance its functionality as a Python Object Graph Mapper (OGM), similar to SQLAlchemy for relational databases. This update simplifies the process of working with graph databases by allowing users to store Python objects directly into a graph database without using Cypher, and it includes automatic schema validation, serialization, and deserialization. It also offers on-disk storage solutions for large properties, enabling the storage of extensive data without managing separate storage solutions. Additionally, GQLAlchemy now supports integration with streaming and triggers, allowing users to handle data streams and database triggers programmatically in Python. Future plans for GQLAlchemy include supporting the execution of Python functions within a graph database, which will enable the setup of custom triggers and modules.

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