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The Lakehouse Ends the Warehouse-vs-Lake Trade-Off.

Warehouse-grade governance and transactions on cheap object storage, with no duplication. This guide lays out the architecture, the open table formats, the medallion pattern, the economics, and a clean migration path.

In depth

You Have Been Paying Twice for Two Versions of the Truth.

01

Run both, copy data between them, pay for storage and compute twice, and reconcile two versions of the truth.

02

Layer open table formats and a catalog over object storage so one governed copy serves every engine.

The detail

The Three Layers Every Data Platform Needs.

Zone · 01

The Open Table Format

ACID transactions, schema evolution, and time travel on top of plain files in object storage.

Zone · 02

The Catalog

A central catalog handles schema, permissions, discovery, and lineage across engines.

Zone · 03

Decoupled Object Storage

Cheap, durable, infinitely scalable storage that separates storage from compute.

By the numbers

The figures that make it a board-level conversation.

$30-50 per TB/year
Lakehouse storage cost, versus $500-2000 for a traditional warehouse
56%
Of adopters expect to save more than 50% on analytics
67%
Of organizations expect to adopt a lakehouse by 2028
Inside the report

What you'll take away.

01

Step 1 - Pick the open table format

For most enterprises, choose Iceberg for vendor neutrality and broad engine support across Snowflake, AWS, BigQuery, and Databricks. Decide once; it is the foundation everything else sits on.

02

Step 2 - Stand up storage, format, and catalog

Object storage plus the table format plus a governance catalog is the lakehouse core.

03

Step 3 - Implement the medallion layers

Bronze preserves raw, append-only source data as the system of record and replay point.

04

Step 4 - Migrate workloads and point every engine at one copy

Move analytics onto the lakehouse use case by use case, stop copying data into a separate warehouse, then retire the redundant warehouse-plus-lake copies.

Questions

Frequently asked.

Is the data warehouse dead?
Iceberg or Delta?
What is the medallion architecture?
How much will we actually save?
Where do we start?
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Next step

One Governed Copy, Every Engine, A Tenth of the Cost.

Talk through how this applies to your roadmap with our engineering leads - a working session, not a sales pitch.

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