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Documentation Index

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External Tables External Tables are tables backed by StreamNative topics but represented in open table formats, such as Apache Iceberg or Delta Lake, with both data and metadata stored directly in user-managed object storage. Key Characteristics
  • Open Table Formats - Data is written as Parquet files and managed using Iceberg or Delta metadata logs.
  • Object Storage–Backed - Tables reside in S3, GCS, Azure Blob, or other object storage systems.
Externally Managed StreamNative Cloud materializes the data, but table lifecycle, optimization, schema governance, and cataloging are typically managed by a Lakehouse vendor, such as:
  • Databricks Unity Catalog
  • Snowflake Open Catalog
  • Amazon S3 Tables
High Interoperability External Tables are fully queryable by external compute platforms, BI tools, and SQL engines. When to Use External Tables
  • You want deep integration with an existing Lakehouse platform.
  • You require open, interoperable formats for analytics, AI/ML, or downstream workloads.
  • You prefer to manage optimization (compaction, vacuum, retention) in systems like Databricks, Snowflake, or Polaris.