PDE Storing the Data Practice Question
A team needs to run hybrid transactional/analytical workloads on PostgreSQL-compatible data with low latency. They require high performance on both OLTP and OLAP queries, leveraging a columnar engine. Which Google Cloud service is best suited?
⚠ Common exam trap
Candidates often confuse BigQuery's columnar storage with PostgreSQL compatibility, or assume Cloud SQL's PostgreSQL support is sufficient for HTAP workloads, overlooking the need for a dedicated columnar engine.
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
✓
AlloyDB
AlloyDB is the correct choice because it is a fully managed PostgreSQL-compatible database service on Google Cloud that combines a columnar engine for fast analytical queries with high transactional performance. It uses a columnar query accelerator to offload analytical workloads from the transactional engine, enabling low-latency hybrid transactional/analytical processing (HTAP) without data movement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
AlloyDB
Why this is correct
AlloyDB satisfies the hybrid transactional/analytical requirement through its columnar engine, which accelerates OLAP scans while retaining row-based OLTP performance on PostgreSQL-compatible data. This delivers the low-latency analytics alongside transactional throughput that the team needs, unlike Cloud SQL or standard PostgreSQL offerings lacking an integrated columnar accelerator.
- ✗
Cloud SQL for PostgreSQL
Why it's wrong here
Cloud SQL for PostgreSQL provides PostgreSQL compatibility and low-latency transactions but stores data in row format, so it cannot leverage a columnar engine for OLAP acceleration. It suits conventional OLTP deployments where analytical queries are offloaded elsewhere, not hybrid HTAP workloads.
- ✗
Cloud Spanner
Why it's wrong here
Cloud Spanner is a globally distributed relational database with its own SQL dialect, not PostgreSQL-compatible, and it lacks the columnar engine required for HTAP analytical acceleration. It suits horizontally scalable, strongly consistent transactional workloads spanning regions, not hybrid OLTP/OLAP on PostgreSQL.
- ✗
BigQuery
Why it's wrong here
BigQuery is a serverless analytical warehouse optimised for large-scale OLAP scans, not low-latency transactional writes, and it does not expose a PostgreSQL-compatible transactional interface. It fits pure analytics and data-warehouse workloads where sub-second OLTP inserts are not required.
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