Lakehouse vs Warehouse vs Eventhouse: How to Choose

Microsoft Fabric gives you three places to keep data: a lakehouse, a warehouse and an eventhouse. They all store their tables in OneLake. The real question is which engine you want to work with.

Store	Holds	Work with it in	Best for
Lakehouse	files and Delta tables, any shape	Spark and notebooks; the SQL endpoint reads, not writes	data engineers, mixed data
Warehouse	tables only	full T-SQL: insert, update, delete, with transactions	SQL teams
Eventhouse	events and logs, time series	KQL; ingests in seconds	real time at scale

Choose by skills and shape, not size

Choose by the skill of the team and the shape of the data. Size is not the deciding factor: all three scale.

One copy, many engines

Spark reads them, SQL reads them, and Power BI reads them directly with Direct Lake. No engine needs its own copy.

An exam-style question

A team that knows only T-SQL must load tables with INSERT and UPDATE statements, and needs transactions that span several tables. Which store?

Answer: the warehouse. Only the warehouse offers full read and write T-SQL with multi-table transactions. The SQL endpoint of a lakehouse is read-only.

Quick rules

• Spark people, files and tables together? Lakehouse.
• SQL people who write with T-SQL? Warehouse.
• Events arriving every second, queried with KQL? Eventhouse.
• Many real solutions use more than one, all reading the same OneLake data.