ARA-C01 Snowflake Architecture Practice Question
Which of the following describes the 'Multi-cluster' feature of Snowflake Virtual Warehouses?
⚠ Common exam trap
Candidates often confuse multi-cluster warehouses with scaling up (increasing warehouse size). They incorrectly assume multi-cluster warehouses increase performance for a single complex query rather than handling high concurrency by adding more clusters.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The ability to automatically add more compute clusters to handle high concurrency.
Multi-cluster warehouses are designed to handle high concurrency by automatically adding or removing clusters of the same size based on the number of queued queries. This horizontal scaling ensures that as more users run queries simultaneously, the system can maintain consistent performance without requiring manual intervention or scaling up to a larger warehouse size.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The ability to automatically add more compute clusters to handle high concurrency.
Why this is correct
Multi-cluster warehouses solve the problem of concurrency by allowing Snowflake to spin up additional identical clusters of nodes. This ensures that queries from many different users can run in parallel without being queued, providing a consistent experience during peak usage periods while scaling back down when demand decreases.
- ✗
The ability to increase the RAM and CPU of a single cluster for complex queries.
Why it's wrong here
Increasing the RAM and CPU of a single cluster is known as 'scaling up' or vertical scaling, which is achieved by changing the warehouse size (e.g., from Small to Medium). Multi-cluster warehouses, in contrast, focus on horizontal scaling to improve concurrency rather than the raw processing power of an individual query.
- ✗
The ability to run a single query across multiple different Snowflake regions.
Why it's wrong here
Snowflake queries are confined to a single region and a single warehouse. While you can replicate data across regions, a single query cannot span multiple regions or use compute resources from different regions simultaneously. Multi-cluster refers to multiple sets of compute nodes within the same region and account.
- ✗
The ability to join data from multiple different cloud providers in one query.
Why it's wrong here
Snowflake does not support 'cross-cloud' queries where a single query joins data residing natively in different cloud providers (e.g., AWS and Azure). Data must be in the same Snowflake account (and thus the same cloud and region) or accessed via external stages within that same regional context.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
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