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Use case
Experience Snowflake’s fastest query engine on open table formats, with support for advanced data types and optimized query performance.
Overview
Querying across multiple data lakes can be complicated — debugging can be painful and performance bottlenecks lurk everywhere. Snowflake allows you to connect data silos across your architectures with zero data movement, even when that data sits on Parquet files or Iceberg or Delta tables.
Directly connect, transform, optimize and unify data across catalogs and formats, regions and clouds, and share governed access to data products, AI models and apps with any stakeholder.
Deliver more AI and advance analytics innovation using the languages and interfaces you like, with a serverless, auto-scaling engine. Enjoy world-class price for performance on nearly any Iceberg table.
Comprehensively secure and govern your Snowflake environment. Implement FGAC, privacy and compliance controls out of the box to easily protect all your data assets.
Benefits
Fast analytics on data anywhere
Effortlessly access data and powerful insights with an integrated platform and engine. Extend the power of Snowflake's fully managed, unified query engine to open formats, allowing advanced analytics, such as forecasting, anomaly detection, sentiment analysis and time series analysis, on complex data types like VARIANT and geospatial — across all your data sources, wherever they reside.
Harmonize your data
Develop AI data agents and define ML workflows with a comprehensive suite of AI services built on the same governance framework as the data. Use Snowflake’s fully managed Cortex AI service to deliver AI- and ML-powered insights faster.
Analyze at enterprise speed
Analyze in near-real-time thanks to dashboards and applications with a zero-tuning compute engine that just works. Achieve 2X faster query performance¶ on Apache Iceberg tables by extending our leading analytics engine to open table formats.
¶TPC-DS benchmark improvement based on our sampling-based NDV estimation.
WHOOP Improves AI/ML Financial Forecasting While Enhancing Members’ Experiences
With Snowflake and Apache Iceberg, WHOOP teams have centralized access to data while reducing complexity, lowering costs and improving critical processes like feature development and financial forecasting.
Choose your catalog
Govern and discover data across your entire architecture with a connected catalog experience through Snowflake Horizon Catalog and Snowflake Open Catalog. Implement precise security with table, row and column-level access controls for compliance. Alternatively, integrate your any Iceberg REST API catalog seamlessly.
Get Started
Lakehouse Analytics
Most common questions about Snowflake's approach to data lakehouse analytics, including querying data in place, managing Iceberg tables and using open catalog solutions.
A data lakehouse integrates the cost-effective scalability and flexibility of a data lake, ideal for storing diverse raw data, with the robust data management, governance, and high-performance analytics features typically found in a data warehouse.
Snowflake allows you to analyze data stored directly in your external cloud storage (like Amazon S3, Azure Blob Storage or Google Cloud Storage) without needing to move or copy it into Snowflake. This is primarily done using:
The main difference lies in who manages the Iceberg table's metadata (catalog) and lifecycle.
Snowflake-managed Iceberg Tables: Snowflake Horizon catalog manages and performs operations like compaction. This offers a tightly integrated experience with read/write access directly from Snowflake. For multi-engine read access, sync these tables with Snowflake Open Catalog.
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* Private preview, † Public preview, ‡ Coming soon
