ARA-C01 Performance Optimization Practice Question
Which Snowflake feature helps minimize query latency by avoiding re-computation for identical queries?
⚠ Common exam trap
Candidates often confuse the Result Cache with the Warehouse Cache (Local Disk Cache). Result Caching is specific to identical query results, whereas Warehouse Cache stores data blocks.
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
✓
Result Caching.
The Result Cache is an automatic, managed feature that stores the output of identical queries. When a user runs the exact same query again, Snowflake retrieves the result directly from the cache rather than re-computing it. This provides near-instantaneous performance for repeated workloads and is a key component of Snowflake's performance optimization strategy, reducing both latency and unnecessary compute costs for end users.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Query Acceleration Service.
Why it's wrong here
The Query Acceleration Service is designed to speed up long-running, compute-intensive queries by offloading portions of the scan or aggregation to additional compute resources. It does not provide the performance benefit of result caching, which is aimed at eliminating computation entirely for repetitive queries that have already been executed.
- ✓
Result Caching.
Why this is correct
Result caching is a native feature that automatically stores query results in a cache. Subsequent execution of the same query retrieves the saved results, completely avoiding the need for compute resources. This is one of the most effective ways to optimize performance for repetitive dashboard or reporting queries.
- ✗
Materialized Views.
Why it's wrong here
Materialized views are pre-computed data sets that are updated automatically. While they significantly speed up queries, they require explicit definition and have specific maintenance costs. They are not a passive, automatic mechanism like result caching, which handles identical queries without requiring any configuration or additional storage overhead.
- ✗
Automatic Clustering.
Why it's wrong here
Automatic clustering is a data management feature that organizes table data to improve scan performance. It does not store query results or prevent re-computation. Its goal is to make the retrieval of data from the raw tables as fast as possible, rather than bypassing the execution engine for cached results.
About these practice questions
This ARA-C01 question is part of Courseiva's 209-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.