A New Era for Open Data Formats

Snowflake has announced the general availability of Snowflake Storage for Apache Iceberg on both AWS and Azure, marking a significant shift in how enterprises can build open, interoperable data lakehouses. This development combines Snowflake’s enterprise reliability and governance capabilities with the flexibility and openness of Apache Iceberg, one of the most promising open table formats in the data ecosystem.

What is Snowflake Storage for Apache Iceberg?

Snowflake Storage for Apache Iceberg enables users to query and manage Iceberg tables using Snowflake’s SQL engine while storing data in their own cloud object storage. This is fundamentally different from traditional Snowflake architectures—you get:

  • Enterprise reliability - ACID transactions, schema evolution, and time travel
  • Governance and security - Role-based access control, data masking, and audit logging
  • Interoperability - Query Iceberg tables from any Apache Iceberg-compatible tool
  • Cost flexibility - Use your own cloud storage while leveraging Snowflake’s compute

Why This Matters

1. Breaking Vendor Lock-In

For years, one of the key criticisms of traditional data warehouses was vendor lock-in. Data stored in proprietary formats couldn’t easily migrate to competing platforms. With Iceberg and Snowflake Storage, you get enterprise-grade performance without sacrificing portability—your data remains in an open format that other tools can access.

2. Unified Analytics

Organizations often juggle multiple tools for different use cases: Spark for ETL, Python for ML, Snowflake for BI. With Iceberg as a shared format, you can read and write the same tables across all these tools, eliminating costly data movement and synchronization.

3. Cost Optimization

By storing data in your cloud account’s object storage while using Snowflake for compute, you can optimize costs. You pay for Snowflake’s processing power only when you need it, while benefiting from cheaper long-term storage in S3 or Azure Blob Storage.

How It Works

When using Snowflake Storage for Apache Iceberg:

  1. Data remains in your cloud storage - Your S3 buckets or Azure containers stay under your control
  2. Snowflake manages metadata and transactions - Iceberg’s metadata layer ensures ACID guarantees
  3. Query through Snowflake SQL - Use familiar SQL syntax with Snowflake’s optimization engine
  4. Access from multiple tools - Any Iceberg-compatible tool can access the same tables

Enterprise Governance at Scale

One of the most compelling aspects is the governance model. Organizations can now:

  • Apply Snowflake’s Dynamic Data Masking to Iceberg tables
  • Implement tag-based governance across open data formats
  • Use Role-Based Access Control consistently
  • Maintain audit logs of all data access

This brings enterprise data governance to the open data ecosystem, addressing a major pain point for organizations moving toward data lakes.

Availability and What’s Next

Snowflake Storage for Apache Iceberg is now available on:

  • AWS - Via AWS S3
  • Azure - Via Azure Data Lake Storage

The availability on both major cloud platforms is significant—it reflects the industry’s move toward multi-cloud architectures where data strategies shouldn’t lock you into a single provider.

Implications for Data Architecture

This announcement signals several important trends:

  1. The lakehouse wins - The convergence of data warehouse and data lake capabilities continues, with open formats playing a central role
  2. Interoperability is now essential - Enterprises expect their tools to work together seamlessly
  3. Governance is table stakes - Open formats without enterprise governance capabilities aren’t sufficient anymore

Getting Started

If you’re considering Snowflake Storage for Apache Iceberg:

  • Review the requirements for your cloud provider (AWS or Azure)
  • Evaluate existing Iceberg workloads or consider migrating from proprietary formats
  • Assess how Iceberg’s schema evolution and ACID transactions align with your use cases
  • Plan your governance strategy using Snowflake’s tag-based frameworks

Resources

Conclusion

Snowflake Storage for Apache Iceberg represents a maturation of the data lakehouse concept. By combining enterprise reliability with open data formats, it offers organizations the best of both worlds—governance and performance without vendor lock-in. For teams already using Snowflake or investing in Apache Iceberg, this capability opens new architectural possibilities for modern data platforms.