Design innovative, scalable, and highly available cloud database solutions →mediumMultiple ChoiceObjective-mapped
PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
An organization needs to run both transactional (OLTP) and real-time analytical (OLAP) queries on the same dataset without data duplication. The dataset is moderately large (a few terabytes). Which Google Cloud database service is MOST appropriate for this HTAP workload?
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 a fully managed PostgreSQL-compatible database designed for hybrid transactional and analytical processing (HTAP). It includes a built-in columnar engine that accelerates analytical queries on transactional data without separate ETL or duplication.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Bigtable
Why it's wrong here
Bigtable is a NoSQL store, not suitable for transactional SQL workloads or complex analytics.
- ✗
BigQuery
Why it's wrong here
BigQuery is a data warehouse for analytics, not designed for transactional (OLTP) workloads.
- ✓
AlloyDB
Why this is correct
AlloyDB is purpose-built for HTAP with its columnar engine for fast analytics on transactional data.
- ✗
Cloud SQL for PostgreSQL
Why it's wrong here
Cloud SQL does not have a columnar engine and is not optimized for analytical queries.
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Same concept, more angles
3 more ways this is tested on PCDE
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which Google Cloud database service is designed for hybrid transactional and analytical processing (HTAP) with a built-in columnar engine?
easy- A.BigQuery
- B.Cloud SQL
- C.Cloud Spanner
- ✓ D.AlloyDB for PostgreSQL
Why D: AlloyDB for PostgreSQL is a fully managed database with a columnar engine that accelerates analytical queries on transactional data. Cloud Spanner offers an analytics interface, but AlloyDB explicitly mentions a columnar engine for HTAP.
Variation 2. A company needs to perform real-time analytics on streaming data from IoT devices with millisecond latency for alerts, and also run complex historical analytics. Which Google Cloud database architecture supports both?
medium- A.Cloud Bigtable for real-time and BigQuery for analytics
- B.Cloud SQL (read-only replica) for analytics
- C.Cloud Spanner with interleaved tables
- ✓ D.AlloyDB with columnar engine
Why D: AlloyDB with columnar engine handles real-time inserts and fast analytical queries on the same data, ideal for HTAP workloads.
Variation 3. A company is migrating a monolithic application to Google Cloud and needs to modernize the database layer. The application has both OLTP (high-volume transactions) and OLAP (complex reporting) workloads. The team wants to use a single database to simplify operations but with high performance for both. Which TWO Google Cloud database services support hybrid transactional/analytical processing (HTAP)? (Choose two.)
medium- A.Cloud Bigtable
- B.BigQuery
- ✓ C.AlloyDB
- ✓ D.Cloud Spanner
- E.Cloud SQL
Why C: AlloyDB with columnar engine and Spanner with analytics interface support HTAP. Cloud SQL and Bigtable do not natively support HTAP. BigQuery is purely analytical.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCDE practice question is part of Courseiva's free Google Cloud 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 PCDE exam.