Overview

This section explains how to connect Bauplan‑managed Iceberg tables in your object storage to other platforms your teams already use, such as Snowflake, Databricks Unity Catalog, AWS Glue and Athena.

Bauplan writes tables in Apache Iceberg format and exposes a standards-compliant Iceberg REST catalog. External engines discover tables through that catalog and read files directly from your bucket with their own cloud credentials.

Option 1: External catalogs (recommended)

Most modern engines now support the Iceberg REST catalog. This lets them attach directly to Bauplan and see all namespaces and tables, with no manual refresh required.

• Bauplan catalog endpoint

  https://api.use1.aprod.bauplanlabs.com/iceberg

  Auth: Bearer <token> (we recommend a read-only Bauplan user)

• Storage

  Your object store (i.e. Amazon S3).

  Engines authenticate with their own IAM/service accounts.

• Engines supported

  Snowflake Open Catalog, Databricks Unity Catalog, BigQuery, Trino, Athena, Spark, DuckDB, and others with native Iceberg connectors.

See dedicated guides for Snowflake, Databricks, Athena, and more below.

Option 2: External tables (per-table)

If your engine does not yet support the REST catalog, you can still integrate by registering each table directly from its metadata location.

• Use Bauplan’s API (client.get_table(...)) to retrieve the Iceberg metadata path.
• Register that path manually in your engine as an external table.
• You must refresh tables manually when schema or snapshots change.

This approach works everywhere, but requires more operational overhead than catalog integration.

Summary

• External catalog: plug-and-play, auto-discovery, recommended whenever supported.
• External tables: manual, per-table setup, fallback for engines without catalog support.

Bauplan ensures that whichever route you take, your tables remain in open formats on your own storage, accessible to the rest of your stack.