Snowflake expands its collaboration with Google Cloud to integrate Google's Gemini 3 AI models directly into Snowflake Cortex AI, enabling enterprise-ready AI on Snowflake’s governed data platform.

New regional deployments are planned for Snowflake on Google Cloud in the Kingdom of Saudi Arabia and Melbourne, Australia, with Melbourne expected in early 2026 to meet rising demand.

Snowflake Gen2 Warehouses on Google Cloud Axion-based C4A VM machines become production-ready, delivering notable price-performance benefits.

The article provides a company overview and does not include external market data or performance metrics beyond basic capability descriptions.

The compute layer allocates dedicated resources to support multiple users accessing common data sets for diverse use cases with minimal latency.

The storage layer ingests large volumes of structured, semi-structured, and unstructured data to create a unified data record for analytics and AI.

ClearQuery enables rapid data exploration and analysis through natural language queries.

Snowflake employs a headcount of over 9,000 employees.

Snowflake emphasizes a consumption-based, customer-centric model focused on scalability and flexible usage.

The platform uses a multi-layer, cloud-native architecture with independently scalable compute, storage, and cloud services to support low-latency access and scalability.

Snowflake positions itself as a data cloud and AI company delivering an AI Data Cloud by consolidating data into a single source of truth for insights, AI apps, data products, and collaboration.

Snowflake markets itself as a leading AI data platform with more than 12,600 customers globally, underscoring enterprise-ready AI capabilities.