An Architect's Guide

to Multi-Engine

Lakehouses: What's

Solved and What Isn't

The multi-engine lakehouse is where the industry is heading. Apache Iceberg has made the vision real: Store data once in an open format, attach the right engine for each job and stop maintaining endless pipelines between siloed systems.

But "mostly solved" is not the same as "fully solved." Organizations that treat current interoperability claims as complete typically discover the shortcomings after they've already made architectural commitments that aren't easy to unwind.

This guide is a field assessment from Jason Hughes and Jim Lebonitte, two Snowflake platform architects with direct experience helping enterprises navigate these decisions. It covers three dimensions of interoperability — data, business logic and governance — with honest analysis of what's mature, what's still in progress and what you need to know before going to production.

What you'll find inside:

• A breakdown of Apache Iceberg v2 and v3 feature support across major engines — and why "supports v3" requires follow-up questions
• The business logic problem most teams discover too late: why the same Iceberg table can produce different results in different engines, and what to do about it
• Where fine-grained access control and row/column-level security are still not standardized across platforms, and the implications for compliance
• Practical architecture guidance on where simultaneous multi-engine access pays off today and where a single-engine approach remains the lower-risk path
• What Iceberg, Apache Polaris and Apache Ossie are working toward — with specific proposals and timelines to track