Google Cloud has announced that its Spanner Graph is now generally available (GA). It includes new capabilities such as Graph Notebook, GraphRAG with LangChain integration, Graph schema in Spanner Studio, and Graph query improvements by supporting path data type and functions.
Spanner Graph builds on Cloud Spanner, Google’s fully-managed, scalable, and highly available database. Hence, users can benefit from the same high availability, global consistency, and horizontal scalability.
Last August, the company introduced the database as a unified one that seamlessly integrates graph, relational, search, and AI capabilities with virtually unlimited scalability. The initial release offered an intuitive Graph Query Language (GQL) interface for pattern matching, full graph and SQL model interoperability, built-in search capabilities, and deep integration with Vertex AI for accelerated insights.
The new capabilities with the GA release are:
- A Spanner Graph Notebook that enables users to visually query and explore Spanner Graph data using GQL syntax within notebook environments like Google Colab and Jupyter Notebook, offering tools for graph schema visualization, tabular result inspection, various layout options, and easy integration.
- The integration of GraphRAG with LangChain and Neo4j, which enhances AI applications by combining knowledge graphs and Retrieval-Augmented Generation to facilitate efficient querying and natural language interactions with graph-based data.
- The Graph Schema in Spanner Studio that enables users to design, visualize, manage, and update graph schemas in Google Cloud Spanner using SQL/PGQ, offering best practices for efficient graph design and maintenance.
- Support for the path data type and functions, enabling users to analyze sequences of nodes and relationships, as demonstrated by the ability to check for acyclic paths in a graph query.
- Integration with leading graph visualization partners like GraphXR allows users to utilize advanced visualization technology and analytics to understand complex data better.
(Source: Google blog post)
Spanner Graph is designed to handle large-scale graph data workloads, making it ideal for applications that require real-time analysis of complex relationships. This includes use cases such as fraud detection, recommendation engines, and financial investments.
Kinevez, the company that has its visual GraphXR tool integrated with Spanner Graph, tweeted:
With improved search and built-in AI features, Spanner Graph can transform how businesses leverage connected data—whether in financial investing, fraud detection, or customer 360.
In addition, Abdul Rahim Roni commented on a LinkedIn post by Google:
This is an exciting leap forward, Google Cloud. Integrating graph, relational, and generative AI capabilities under Spanner Graph truly redefines database management. Incredible work in pushing the boundaries of innovation.
Lastly, more details are available on the documentation pages.
