CDC Without Complexity Using Iceberg v3 Row Lineage
Iceberg v3 row lineage adds _row_id and _last_updated_sequence_number to every table, enabling native change data capture without Debezium or Kafka.
The archive
Writing, page 26
657 posts on Apache Iceberg, lakehouse architecture, data engineering and applied AI.
The 2026 Guide to Iceberg View Federation
Iceberg views standardize SQL view definitions across engines, enabling view federation across Polaris, Nessie, and Gravitino catalogs.
Implementing MCP in the Lakehouse
How to build a Model Context Protocol (MCP) server that exposes lakehouse tables and semantic views as AI-accessible tools, with Python implementation.
Microsoft Fabric Build 2026 Agentic Analytics Stack
Microsoft Build 2026 revealed an agentic analytics stack built on Fabric IQ, OneLake Iceberg support, and semantic models.
Modern Python Tooling for Apache Iceberg
PyIceberg, IceFrame, and the Iceberg CLI form a complete Python toolchain for Iceberg table management.
REST Catalog Credential Vending for Lakehouse Security
Iceberg REST catalog credential vending issues short-lived, table-scoped storage tokens for S3, ADLS, and GCS.
SaaS Buyers Now Inspect Your Semantic Layer
Enterprise SaaS procurement in 2026 evaluates how platforms expose data to AI agents. Semantic layers have become a decision criterion alongside.
Securing Agent Identities in the Lakehouse
How OAuth 2. 0 token exchange, OAuth 2. 1 device authorization grant, credential vending, and fine-grained access control secure AI agent identities.
Bidirectional Iceberg Writes with Horizon Catalog
Snowflake Horizon Catalog enables bidirectional Iceberg writes from external engines like Spark and Trino, powered by Apache Polaris.
Semantic View Autopilot in Snowflake Semantic Studio
Snowflake Semantic View Autopilot automates semantic view creation from query history and BI assets.