Question 924 of 919
DP-300 Columnstore index Practice Question
Your Azure SQL Database is running in the General Purpose tier. You notice that read queries are experiencing high latency. You need to improve read performance without changing the compute size. What should you implement?
⚠ Common exam trap
Candidates may assume read scale-out is available in General Purpose or confuse 'compute size' with 'service tier'. While the question only forbids changing compute size, read scale-out is not supported on General Purpose, making it an invalid choice. Columnstore indexes are a viable option that does not require tier changes.
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
✓
Create columnstore indexes on the tables
Creating columnstore indexes can improve read performance by compressing data and enabling batch processing for analytical queries, which reduces I/O and latency without requiring a change in compute size or service tier. Read scale-out (option B) is not available on the General Purpose tier, so it cannot be implemented without upgrading to a higher tier, which might be considered a change beyond compute size. Hyperscale (option A) changes the service tier and may not directly address read latency. In-memory OLTP (option D) is optimized for transactional workloads, not general read queries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Upgrade to the Hyperscale service tier
Why it's wrong here
Upgrading to Hyperscale changes the service tier and may not directly improve read latency; it is not the most straightforward solution under the constraint.
- ✗
Enable read scale-out
Why it's wrong here
Read scale-out requires the Business Critical or Hyperscale tier; it is not supported on General Purpose, so it cannot be enabled without changing the service tier.
- ✓
Create columnstore indexes on the tables
Why this is correct
Columnstore indexes improve read performance for analytical queries by compressing data and using batch execution, reducing I/O and latency without changing compute size or tier.
- ✗
Use in-memory OLTP for the tables
Why it's wrong here
In-memory OLTP is designed for high-concurrency OLTP workloads, not for general read latency reduction.
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Last reviewed: Jun 24, 2026
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