Surviving Commit Conflicts When Dozens of Writers Hit the Same Iceberg Table
Commit conflicts multiply with writer count, and AI agents introduce unpredictable write patterns.
The archive
652 posts on Apache Iceberg, lakehouse architecture, data engineering and applied AI.
Commit conflicts multiply with writer count, and AI agents introduce unpredictable write patterns.
Jackson 3 changes everything: package names, unchecked exceptions, flipped defaults. Here's what breaks, why the engines are fine and your service isn't.
The catalog is the right attachment point for AI agents working against a lakehouse. Here's how to wire the official Polaris MCP Server and add the read.
Catalog federation gives you one authorization model and one audit point across regions. Here's what it solves, what it doesn't, and how to build.
Federate first so analytics work now, migrate what benefits from migrating, and leave the rest where it is indefinitely.
Parquet files have a version field that doesn't reliably signal feature requirements. A new versioning discipline is coming, borrowing from Iceberg's.
A large share of production transformations fit comfortably on one machine. PyIceberg, DuckDB, and branch isolation give you a production path that debugs.
Agents break the four assumptions analytics platforms were built on. A practical guide to identity, budgets, semantic layers, caching, and instrumentation.
A full survey of the AI model landscape in mid-2026: frontier families, open-weight labs, local inference, specialists, and how to build a routing layer.
Data freshness needs to become an engineering contract with a measurable value, an owner, and consequences.