Understanding the relationships within your data is crucial for uncovering hidden insights and building intelligent applications. However, managing operational (OLTP) and analytical (OLAP) graph workloads usually means wrestling with disconnected databases, building brittle data pipelines, and managing complex integrations. This fragmentation creates data silos, increases operational overhead, and limits scalability.
Today, we’re thrilled to introduce a unified graph database and analytics solution powered by Spanner Graph and BigQuery Graph. The solution consists of the two platforms, recommended blueprints for how to deploy them, and getting started guides for the most prominent use cases. In this blog, we review the solution’s components, provide an overview of the most common use cases, and hear from customers who have deployed the solution in the real world.
Spanner Graph for operational workloads
Spanner Graph reimagines graph data management, bringing together graph, relational, search, and generative AI capabilities into a single database. It is backed by Spanner’s signature unlimited scalability, high availability, and strong consistency.
With Spanner Graph, you get:
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Integrated table-to-graph mapping: Define graphs directly over your existing Spanner relational tables, allowing you to view and query operational data as a graph without data duplication.
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Interoperable graph and relational querying: Leverage an ISO-standard Graph Query Language (GQL) interface for intuitive pattern matching, and mix GQL with SQL in a single query to traverse both graph and tabular data together.
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Advanced search and AI integration: Utilize built-in vector search, full-text search, and Vertex AI integration to retrieve data by semantic meaning and power intelligent applications directly within your database.
Customers are already using Spanner Graph to power high-throughput, low-latency applications – for identity resolution across millions of entities, identifying dependencies across vast complex environments, data lineage, customer 360 use-cases, and enhancing real-time fraud detection.
“Open Intelligence is our foundational intelligence layer that securely connects trillions of live data points from clients, partners and WPP in a privacy-first way and is now integrated and powers WPP’s agentic marketing platform, WPP Open. Enabled by Google Cloud’s Spanner Graph, Open Intelligence is a significant advancement in AI-driven marketing and we are excited about extending the use case for analytical graph workloads on BigQuery Graph.” – Rob Marshall, Head of Strategy, Data & Intelligence, WPP
BigQuery Graph for analytical workloads
While Spanner Graph handles your active operations, true large-scale analysis requires exploring relationships across billions of nodes and edges to identify patterns and query historical data. Just as SQL relies on distinct tools for databases and data warehouses, the graph landscape requires specialized tools for different workloads. That’s why we built BigQuery Graph.
BigQuery Graph brings connected data analytics directly into your data warehouse. You can map existing BigQuery data to a graph schema and query it with SQL or GQL to uncover hidden relationships in massive datasets – without moving any data.
Key capabilities include:
- Integrated table-to-graph mapping: Map your existing BigQuery tables to graphs instantly, uncovering hidden relationships in your data warehouse without building ETL pipelines or moving a single byte of data.
- Interoperable graph and relational querying: Apply the same expressive pattern matching of GQL to massive historical datasets, and mix SQL with GQL in a single query to combine the familiarity of your data warehouse with powerful graph traversal.
- Advanced search and AI integration: Leverage native integration with BigQuery AI for predictive analytics, alongside built-in vector search, full-text search, and geospatial functions to locate connected information across billions of records.
Spanner Graph and BigQuery Graph as a unified solution
While each platform is powerful on its own, their true value emerges when they are deployed together. By connecting your operational and analytical environments, you eliminate data silos and accelerate your time-to-insight without compromising database performance.
“Spanner Graph enables Yahoo to unify our data into a connected foundation at a global scale, powering real-time, intelligent decision-making across our agentic advertising platform. This enhances our AI-driven approaches that drive one of the largest digital advertising ecosystems, and we look forward to building on it with BigQuery Graph to unlock deeper analytics and predictive capabilities to power future innovation.” – Gabriel DeWitt, Head of Consumer Monetization, Yahoo
Source Credit: https://cloud.google.com/blog/products/data-analytics/the-unified-graph-solution-with-spanner-graph-and-bigquery-graph/
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