Spanner’s multi-model advantage for agentic ai

In the age of agentic AI, the role of databases is fundamentally changing. It’s evolving from a passive data repository into an intelligent, active context hub designed to ground generative AI foundation models and a reasoning engine that drives proactive actions. To power sophisticated AI and agentic workflows, a database must do more than store and query your data — it must facilitate reasoning, provide deep contextualization, and turn static intelligence into proactive action – all in a multiple data model environment. 

Rather than manually orchestrating data across disparate silos, a multi-model database approach coalesces relational, vector, and graph data into a rich, unified knowledge base. This allows AI to leverage situational, semantic, and relationship context simultaneously. Spanner, Google Cloud’s globally consistent, scalable, fully managed database, is built for the AI era. It offers a unified approach to integrate your data and power sophisticated, agentic AI.

In this post, we’ll look at how Spanner is helping organizations achieve production-ready AI, and if you want more real-world examples, you can read this companion article. It covers four key areas — fraud detection, personalized recommendations, hybrid search, and autonomous network operations.

The Power of interoperable multi-model databases

Today’s common, fragmented, multi-database strategy introduces critical challenges: 

• Data inconsistency: The absence of a single source of truth forces developers to simulate consistency through brittle application code, leading to data duplication, stale data, and significant governance and security vulnerabilities. Your application’s overall reliability is effectively capped by the database with the lowest SLA.

• Operational and skill silos: Managing disparate systems creates massive operational overhead and fractures your team into skill-silos, imposing a “complexity tax” that directly inflates costs and drags down development velocity.

• Unified intelligence blockers: Inherent data silos and the ETL latency create an architectural barrier, preventing the real-time, context-aware intelligence required to power cutting-edge AI applications.

Together, these challenges create a significant structural disadvantage in the AI era.

Spanner’s AI advantage

We’ve been constantly evolving Spanner over the years, to keep up with the most demanding cloud workloads and Generative AI offers some of the most unique and novel database challenges yet. 

Building on its core foundation, Spanner introduced fully interoperable multi-model capabilities last year, allowing you to access and query your data using diverse models — including relational, key-value, graph, and vector —all within a single, highly capable database foundation. Each data model is powerful in their own right:

• Relational: Spanner has pioneered the relational scale-out database, offering ANSI SQL with both Google SQL and PostgreSQL dialects that delivers 5 9s availability and strong consistency across the globe. 
• Key-value: Spanner also offers high-performance, key-value database capabilities. Its Cassandra native endpoint allows customers to easily lift and shift their Cassandra workload to Spanner without change to application codes
• Graph: Built on the ISO standard GQL, allowing you to model data natively as a graph or as a simple overlay on top of relational data.
• Vector: A fully integrated semantic search solution offering both KNN and ANN, with the latter built using Google’s state-of-the-art ScaNN technology, capable of supporting indexes with over 10 billion vectors.
• Full-Text Search: building on Google’s decades of search expertise that allows you to search for across structured and unstructured data with advanced information retrieval tools out of the box for 40+ languages
• Integration with Data Warehouses: Seamlessly connecting transactional data with insights from analytical processes.

This unified architecture eliminates the need for complex data synchronization across multiple specialized databases, radically simplifying your environment and accelerating development. Customers can now leverage Spanner’s interoperable multi-model capability to combine distinct data types seamlessly.

Companies making AI a globe-spanning success

MakeMyTrip is one of many companies putting AI into production in demanding real-world environments thanks to the multi-model capabilities of Spanner.

An India-based online travel company, MakeMyTrip has successfully consolidated four specialized databases into a single Spanner instance, significantly reducing operational complexity, while accelerating AI innovation and achieving high performant and high quality outputs.

Ravindra Tiwary, director of technology development at MakeMyTrip, saw multiple benefits to her organization’s Spanner migration: “We consolidated MongoDB, Neo4j, Elasticsearch, and Qdrant into one unified system, achieving a 75% reduction in operational complexity. This transition eliminated the friction of managing multiple database nuances and redundant synchronization pipelines.

The most transformative advantage is executing unified queries across lexical, keyword, and embedding searches in a single platform. This consolidation accelerated our feature innovation cycle by 30% to 50% for consolidated-view features and saved 5.5 to 9.5 operational hours per week, per destination.

With Spanner as our single source of truth, we eliminated data drift and ensured facts are updated atomically. This directly improved our answer-quality score by 9%. Spanner now provides the scalable, high-performance foundation essential for our ‘Destination Expert’ ecosystem (a homegrown GenAI-powered travel planner bot providing personalized travel recommendations) and future AI workflows.”  

And they’re not the only ones who’ve reached new destinations on their AI journey. To learn how leading organizations like Target, Palo Alto Networks, and MasOrange are succeeding with Spanner, check out our next post. 

To get started on your own AI journey with Spanner, visit our Spanner page to learn more and get started today.