Written by Alex Merced Developer from devNursery.com and alexmercedcoder.dev You should follow him on Twitter and checkout his articles on LogRocket.
Iceberg views standardize SQL view definitions across engines, enabling view federation across Polaris, Nessie, and Gravitino catalogs. How Snowflake Horizon, Databricks Unity Catalog, and open source catalogs handle portable SQL.
Iceberg v3 row lineage adds _row_id and _last_updated_sequence_number to every table, enabling native change data capture without Debezium or Kafka. Technical deep dive with Snowflake and Databricks examples.
How to build a Model Context Protocol (MCP) server that exposes lakehouse tables and semantic views as AI-accessible tools, with Python implementation patterns and authentication.
PyIceberg, IceFrame, and the Iceberg CLI form a complete Python toolchain for Iceberg table management. Each tool targets a different workflow from metadata inspection to data engineering.
Microsoft Build 2026 revealed an agentic analytics stack built on Fabric IQ, OneLake Iceberg support, and semantic models. The architecture shows how Microsoft competes with open lakehouse platforms.
Iceberg REST catalog credential vending issues short-lived, table-scoped storage tokens for S3, ADLS, and GCS. How Polaris, Snowflake Horizon, Databricks Unity Catalog, and Dremio implement credential vending for secure lakehouse storage access.
