Scott Teal

Apache Iceberg is the standard for data sovereignty and interoperability, but building a high-performance lakehouse is often slowed by complex engineering. Modern data is fragmented across real-time streams, CDC and cloud files. Manually transforming these into a performant Iceberg architecture requires massive effort to manage maintenance, metadata and partitioning. This session shows how Snowflake acts as a universal engine for Iceberg. Learn how Snowflake automates the data lifecycle — from ingestion to continuous optimization — without manual intervention. See how to transform any raw source into governed, production-ready Iceberg tables that stay open and easy to manage at scale.

Have multiple copies of the same data? Learn how Snowflake is delivering interoperability without compromise, making it easier to architect for multi-engine access on a single data copy, across more use cases, with governance policies that persists across engines at the table, row, and column level. In this What's New session we'll cover the latest features expanding what you can do with Iceberg v3, how Snowflake Storage for Apache Iceberg(tm) makes it easy to unlock interoperability without bucket managemnet, new Horizon Catalog capabilities that deliver universal governance for mulit-catalog envrinoments and persisst fine grained access policies across engines, and how to share and access open data within and outside of Snowflake's bounderies.

As data lakes grow, seamless access and strong governance are crucial. However, governance for Apache Iceberg to-date has often ended up fragmented, forming inconsistencies and complex integrations. Apache Polaris simplifies governance for multi-engine architectures with a unified access control layer that integrates with Apache Spark, Trino, Snowflake and more. Join this session to learn more about how Polaris makes this possible along with demos, updates and ways to join the community.