ARA-C01 Snowflake Architecture Practice Question
A Snowflake architect is optimizing a virtual warehouse for a workload that consists of many small, concurrent queries with high concurrency requirements. The queries are simple and return small result sets. The architect wants to minimize queuing and ensure fast response times while controlling costs. Which warehouse configuration should the architect choose?
⚠ Common exam trap
The trap here is assuming that a larger single warehouse can handle high concurrency better, but concurrency is limited by the number of clusters, not just size.
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
✓
A multi-cluster warehouse with Standard scaling policy and a small warehouse size.
A multi-cluster warehouse with Standard scaling policy and a small warehouse size is optimal for many small, concurrent queries. Standard policy adds clusters immediately when queries are queued, reducing latency. Small size keeps costs low for simple queries. This setup ensures high concurrency without over-provisioning compute resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A multi-cluster warehouse with Economy scaling policy and a medium warehouse size.
Why it's wrong here
Economy scaling policy delays adding clusters until it estimates a sustained load, which can lead to queuing during sudden spikes. For many small, concurrent queries, immediate scaling is preferred to minimize latency. A medium warehouse size is also larger than necessary for simple queries, increasing cost without significant benefit. This configuration may not meet fast response times.
- ✗
A single-cluster warehouse with a small warehouse size and increased statement timeout.
Why it's wrong here
A single small warehouse can only handle a limited number of concurrent queries; increasing statement timeout does not reduce queuing and may cause queries to wait longer before failing. This configuration would lead to poor response times under high concurrency. Scaling out with multiple clusters is necessary to handle many concurrent queries efficiently.
- ✓
A multi-cluster warehouse with Standard scaling policy and a small warehouse size.
Why this is correct
A multi-cluster warehouse with Standard scaling policy automatically adds clusters when queries are queued, immediately reducing queuing for high concurrency. A small warehouse size is cost-effective for simple queries with small result sets. This configuration balances performance and cost by scaling out only when needed, making it ideal for many small, concurrent queries.
- ✗
A single-cluster warehouse with a large warehouse size.
Why it's wrong here
A single large warehouse provides more compute power per query but does not handle high concurrency well because it has a fixed number of resources. Many small queries may still queue if they exceed the warehouse's concurrency limits. Additionally, a large warehouse is more expensive and may be overkill for simple queries, leading to inefficient cost.
About these practice questions
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JA
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
This ARA-C01 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the ARA-C01 exam.