Spanner Graph unites purpose-built graph database capabilities with Spanner, which offers industry-leading scalability, availability, and consistency.
Spanner Graph supports a graph query interface compatible with the ISO GQL (Graph Query Language) standards. Spanner Graph supports interoperability between relational and graph models and combines the well-established SQL capabilities with the expressiveness of graph pattern matching from GQL.
You can map tables to graphs using declarative schema without data migration, which brings graphs to tabular datasets. You can also late-bind data model choices per query, which makes it easier to choose the right tool for your workflows.
To get started with Spanner Graph, see Set up and query Spanner Graph and the Spanner Graph codelab.
Benefits of graph databases
Graphs provide a natural mechanism for representing relationships in data. Example use cases for graph databases include fraud detection, recommendations, community detection, knowledge graph, customer 360, data cataloging, and lineage tracking.
Traditionally, this type of graph data is represented as tables in a relational database, with applications using multiple joins to traverse the graph. Expressing graph traversal logic in SQL leads to complex queries that are difficult to write, maintain, and debug.
The graph interface in Spanner Graph lets you navigate relationships and identify patterns in the graph in intuitive ways. In addition, Spanner Graph provides graph-optimized storage and query enhancements suited for online analytical and transactional graph workloads, all built in to Spanner's core capabilities.
This approach makes Spanner Graph the ideal solution for even the most mission-critical graph applications. In particular, Spanner's transparent sharding can scale elastically to very large data sets and use massively parallel processing without user intervention.
Use cases
You can use Spanner Graph to build many types of online Graph applications, including the following:
- Financial fraud detection: Analyze complex relationships among users, accounts, and transactions to identify suspicious patterns and anomalies, such as money laundering and irregular connections between entities, which can be difficult to detect using relational databases.
- Customer 360: Track customer relationships, preferences, and purchase histories. Gain a holistic understanding of each customer, enable personalized recommendations, targeted marketing campaigns, and improved customer service experiences.
- Social networks: Capture user activities and interactions and use graph pattern matching for friend recommendations and content discovery.
- Manufacturing and supply chain management: Use graph patterns for efficient impact analysis, cost rollups, and compliance checks by modeling parts, suppliers, orders, availability, and defects in the graph.
- Health Care: Capture patient relationships, conditions, diagnosis, and treatments to facilitate patient similarity analysis and treatment planning.
- Transportation: Model places, connections, distances, and costs in the graph, and then use graph queries to find the optimal route.
Key capabilities
Spanner Graph introduces a unified database that integrates graph, relational, search, and AI capabilities with high performance and scalability to deliver the following:
- Native graph experience: The ISO GQL interface offers a familiar, purpose-built graph experience that's based on open standards.
- Unified relational and graph: Full interoperability between GQL and SQL breaks down data silos and lets you choose the optimal tool for each use case, without any operational overheads to extract, transform, and load (ETL).
- Built-in search capabilities: Rich vector and full-text search capabilities work organically with graph, letting you use semantic meaning and keywords in graph analysis.
- AI-powered insights: Deep integration with Vertex AI unlocks a suite of AI models directly in Spanner Graph, helping you to accelerate your AI workflows.
- Scalability, availability, and consistency: Spanner's established scalability, availability, and consistency provide a solid foundation that you can trust.
What's next
- Get started with the Spanner Graph codelab.
- Set up and query Spanner Graph.
- Learn about the Spanner Graph schema.
- Create, update, or drop a Spanner Graph schema.