Posts
All the articles I've posted.
- 31 MIN READ•Jul 28, 2026
Why AI Agents Fail on Raw Data, and What to Give Them Instead
Agents fail on raw lake data because business rules live in people's heads. Data products with semantic contracts fix this at the source.
AI AgentsApache IcebergSemantic Layer - 31 MIN READ•Jul 28, 2026
Why Iceberg V4 Wants to Retire Equality Deletes, and What Streaming Teams Should Do About It
Equality deletes made streaming upserts into Iceberg practical at the cost of read performance.
Apache IcebergStreamingData Engineering - 31 MIN READ•Jul 28, 2026
The Five Layers Between Your Lakehouse and a Trustworthy Agent
Agent reliability is a property of the stack the model sits on. Five layers with distinct owners and failure modes turn the agent is unreliable.
AI AgentsApache IcebergData Architecture - 31 MIN READ•Jul 28, 2026
Apache Fluss and Kafka Solve Different Problems in an Iceberg Pipeline
Fluss puts a columnar, indexed hot tier between Kafka and Iceberg. Here's what it changes structurally, what Kafka still does better, and how to benchmark.
Apache IcebergApache FlussKafka - 31 MIN READ•Jul 28, 2026
Serving Sub-Second Queries Over an Iceberg Lakehouse With a Hot Tier
A lakehouse cannot serve sub-second queries over seconds-old data. A hot tier in front solves it, with consequences for consistency, governance.
Apache IcebergStreamingData Serving - 31 MIN READ•Jul 28, 2026
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.
Apache IcebergConcurrencyData Engineering - 31 MIN READ•Jul 28, 2026
The Jackson 3 Problem in Apache Iceberg, and What It Means for Your Code
Jackson 3 changes everything: package names, unchecked exceptions, flipped defaults. Here's what breaks, why the engines are fine and your service isn't.
Apache IcebergJacksonJava - 31 MIN READ•Jul 28, 2026
Wiring an AI Agent to Apache Polaris with the Model Context Protocol
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.
Apache IcebergMCPAI Agents - 31 MIN READ•Jul 28, 2026
Governing Iceberg Tables Across Regions Without Three Sets of Permissions
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.
Apache IcebergApache PolarisData Governance - 31 MIN READ•Jul 28, 2026
Federating Oracle With an Open Lakehouse Instead of Migrating It
Federate first so analytics work now, migrate what benefits from migrating, and leave the rest where it is indefinitely.
Apache IcebergOracleData Federation - 31 MIN READ•Jul 28, 2026
The Parquet Versioning Problem, and Why Iceberg Cares About It
Parquet files have a version field that doesn't reliably signal feature requirements. A new versioning discipline is coming, borrowing from Iceberg's.
ParquetApache IcebergData Engineering - 31 MIN READ•Jul 28, 2026
Building Iceberg Pipelines in Python Without Standing Up Spark
A large share of production transformations fit comfortably on one machine. PyIceberg, DuckDB, and branch isolation give you a production path that debugs.
Apache IcebergPythonPyIceberg