The State of Apache Polaris in July 2026: From Incubating Catalog to the Governance Layer of the Open Lakehouse
I have a personal stake in this one, so let me declare it up front. Apache Polaris was co-created by Snowflake and Dremio, I work at…
The archive
Writing, page 12
578 posts on Apache Iceberg, lakehouse architecture, data engineering and applied AI.
The State of Streaming to Apache Iceberg in July 2026: Every Path, Its Latency, and What to Do When Seconds Are Not Fast Enough
The most common architecture question I get in 2026 is no longer "should we use Iceberg." That one is settled. The question now is "how…
High-Performance Columnar Transfers: Combining Apache Arrow Flight and Iceberg REST Catalogs
Modern lakehouse architecture is easier to reason about when you separate two questions. The first question is how a system discovers and…
Block vs. Object Storage: A Deep Dive Into the Foundation of Modern Data, and How the Lakehouse Made the Slow Option Fast
Here is one of the strangest and most consequential plot twists in the history of data infrastructure: over the past decade, the analytics…
The Buyer's Scorecard for Agentic Analytics: Evaluating Tooling in the Enterprise AI Era
Agentic analytics demos are easy to enjoy and hard to evaluate. A user asks a question, an assistant answers, a chart appears, and the room…
Building Closed-Loop Decision Agents: Moving from Passive BI Dashboards to Active Goal-Directed Workflows
Dashboards are excellent at showing people what happened. They are less good at deciding what should happen next. That gap is where…
Conversational AI on Managed Iceberg: Exposing Amazon S3 Tables through MCP
The most interesting part of conversational analytics is not the chat box. The chat box is just the surface area. The harder question is…
Decoupled Catalogs vs. Managed Tables: Architectural Freedom in the Age of Table Format Convergence
Open table formats have changed buyer expectations. A few years ago, the question was whether an organization should put more analytical…
Designing Your Own AI Harness: A Deep Dive Into the Architecture of Agent Loops, Tools, Context, and Control
The most underappreciated finding in applied AI this year fits in one statistic: a major framework team took the same model, changed…
Deterministic Data Engineering With AI Harnesses: Using Claude Code, Codex, Antigravity, and OpenCode for Data Work You Can Actually Trust
There is an apparent contradiction at the heart of using AI agents for data work, and resolving it properly is worth an entire article,…