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databricks-iceberg

Manage Iceberg tables in Databricks and expose them to external engines via IRC.

Updated Jan 30, 2026
Search Tags:#iceberg#snowflake#databricks#unity-catalog#irc#external-iceberg-reads#pyiceberg
One-click install
npx skills add https://github.com/teegin-g/Slopcast --skill databricks-iceberg-teegin-g
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-iceberg
Source: https://github.com/teegin-g/Slopcast/tree/main/.agents/skills/databricks-iceberg
Command: npx skills add https://github.com/teegin-g/Slopcast --skill databricks-iceberg-teegin-g

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Apache Iceberg on Databricks presents multiple deployment patterns (Managed Iceberg, UniForm external reads, Compatibility Mode, and IRC-based external access). This Skill describes how to deploy and interoperate Iceberg across Unity Catalog and external engines, including Snowflake facilitation and PyIceberg/OSS Spark integration.

Core Features & Use Cases

  • Native Managed Iceberg tables with full read/write in Databricks.
  • UniForm: making Delta tables readable as Iceberg by external engines without migrating data.
  • Compatibility Mode for streaming tables and materialized views.
  • Iceberg REST Catalog (IRC) enabling external engines to access UC-managed Iceberg data.
  • Iceberg v3: advanced features such as deletion vectors and VARIANT types (beta).
  • Snowflake interop: federated catalog access and cross-platform reads.
  • PyIceberg and OSS Spark clients for external tooling and analytics.
  • Credential vending and EXTERNAL USE SCHEMA grants for secure external access.

Quick Start

Create a managed Iceberg table in Unity Catalog or enable UniForm on a Delta table, then expose it to external engines via IRC and federated Snowflake integrations.

Frequently Asked Questions about databricks-iceberg

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I read Databricks Delta tables as Iceberg from external engines?▼

UniForm makes Delta tables readable as Iceberg by external engines without data migration, enabling cross-engine Iceberg access while maintaining Delta Lake as the source of truth in Unity Catalog.

Can Snowflake read Iceberg tables managed in Databricks Unity Catalog?▼

Yes, Snowflake can access Iceberg tables managed in Databricks Unity Catalog through federated catalog access and Iceberg REST Catalog (IRC) integration, facilitating cross-platform reads.

Do I need Unity Catalog to use managed Iceberg tables in Databricks?▼

Yes, Unity Catalog is required to use managed Iceberg tables in Databricks. It manages the tables and exposes them to external engines via IRC with token-based or OAuth authentication.

What is the Iceberg REST Catalog (IRC) and how does it enable external access?▼

Iceberg REST Catalog (IRC) enables external engines to access Unity Catalog-managed Iceberg data. It uses credential vending and EXTERNAL USE SCHEMA grants for secure external reading.

Can I use PyIceberg and OSS Spark to access Iceberg tables in Databricks?▼

Yes, you can use PyIceberg and OSS Spark clients for external tooling and analytics. They integrate with Unity Catalog-enabled workspaces without installing additional Iceberg libraries.

What Iceberg v3 features are supported in Databricks?▼

Iceberg v3 supports advanced features such as deletion vectors and VARIANT types in beta, enhancing data management capabilities for managed Iceberg tables in Databricks.

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