Google Cloud launched Spanner Graph, an offering to unite purpose-built graph database capabilities with the Spanner database to allow customers to scale beyond trillions of edges.
Standalone graph databases
Although graphs are useful for various use cases, such as fraud detection, recommendation engines, network security, knowledge graphs, customer 360, route planning, data cataloging, and data lineage tracing, adopting standalone graph databases presents challenges.
Some challenges of adopting standalone graph databases include data fragmentation and operational overhead, scalability and availability bottlenecks, ecosystem friction, and skills gaps.
Reimagining graph data management
Spanner Graph aims to reimagine graph data management through a unified database that claims to integrate graph, relational, search, and AI capabilities.
It claims to offer a native graph experience with the ISO Graph Query Language (GQL) interface for matching patterns and traversing relationships. It also offers unified relational and graph models, built-in search capabilities for retrieving graph data using semantic meaning and keywords, Spanner's scalability, availability, and consistency of data foundations, and AI-powered insights deeply integrated with Vertex AI.
"At Credit Karma, ensuring the safety of our 130+ million members' data is our top priority. To combat and eliminate fraud across our systems, we've partnered with Google to enhance our fraud mitigation capabilities by implementing the Spanner Graph Database. This advanced platform capability allows us to detect potential fraud threats before they happen. With Spanner Graph, we effectively detect and prevent fraudulent transactions, account takeovers, and other fraudulent activities," based on a statement released by the Engineering team of Credit Karma.
