A team works in T-SQL and needs multi-table transactions. Which store fits?
Why D is the answer
A warehouse
The warehouse is the T-SQL-first store, and it supports full T-SQL writes.
In detail
- A warehouse gives T-SQL with multi-table transactions.
- Multi-table transactions are a warehouse strength.
Use case
An illustrative scenario, not a real incident.
A finance team loads several related tables in one transaction using T-SQL stored procedures, so a warehouse fits its skills and its needs.
See it in different ways
flowchart TD
A{"Main workload"} -->|"Spark and files"| B["Lakehouse"]
A -->|"T-SQL and transactions on tables"| C["Warehouse"]
A -->|"Streaming and time-series with KQL"| D["Eventhouse"]mindmap
root((Data stores))
Lakehouse
Spark
Files and tables
Warehouse
T-SQL
Transactions
Eventhouse
KQL
Streaming telemetryflowchart TD
Q{"How does the team work?"}
Q -->|"Spark and files"| A0["Lakehouse"]
Q -->|"T-SQL and transactions"| A1["Warehouse"]
Q -->|"KQL and streams"| A2["Eventhouse"]Key point: A warehouse is the T-SQL store.
Why the other options are wrong
- A. A lakehouse with notebooks only
- That is Spark centered.
- B. An eventstream
- An eventstream routes events.
- C. A OneLake shortcut
- A shortcut only links data.