- A
Use a tsvector column with a GIN index on that column
PostgreSQL full-text search with tsvector/GIN is purpose-built for fast ranked search.
- B
Use a separate Elasticsearch instance
Why wrong: External service; not a Cloud SQL schema design.
- C
Use a LIKE '%term%' query with a B-tree index
Why wrong: LIKE with leading wildcard cannot use indexes efficiently; no ranking.
- D
Use materialized view with trigram indexes
Why wrong: Trigram indexes support similarity search but not full-text ranking.
Quick Answer
The answer is to use a tsvector column with a GIN index. This design is correct because PostgreSQL’s built-in full-text search converts text into a tsvector data type, which stores lexemes for efficient linguistic processing, while the GIN (Generalized Inverted Index) accelerates lookups and supports ranking via the ts_rank function. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of native PostgreSQL capabilities versus external services or inefficient pattern matching; a common trap is choosing a trigram index (pg_trgm) for similarity search, which cannot produce relevance-ranked results for full-text queries. Remember that LIKE with wildcards forces a sequential scan and ignores ranking, while external search engines violate the “schema design within Cloud SQL” constraint. Memory tip: think “tsvector for tokens, GIN for gains”—the combination gives you both speed and relevance scoring directly in the database.
PCDE Design and implement database schemas Practice Question
This PCDE practice question tests your understanding of design and implement database schemas. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a schema for a Cloud SQL for PostgreSQL database that supports full-text search across millions of product descriptions. The application requires fast search results ranked by relevance. Which schema design is most appropriate?
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
Use a tsvector column with a GIN index on that column
Option A is correct: use a tsvector column with a GIN index, which is PostgreSQL's built-in full-text search feature optimized for ranking and relevance. Option B uses LIKE with wildcards, which is slow and cannot rank. Option C relies on an external service, not a schema design within Cloud SQL. Option D uses trigram indexes, which support similarity search but not full-text search ranking.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use a tsvector column with a GIN index on that column
Why this is correct
PostgreSQL full-text search with tsvector/GIN is purpose-built for fast ranked search.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a separate Elasticsearch instance
Why it's wrong here
External service; not a Cloud SQL schema design.
- ✗
Use a LIKE '%term%' query with a B-tree index
Why it's wrong here
LIKE with leading wildcard cannot use indexes efficiently; no ranking.
- ✗
Use materialized view with trigram indexes
Why it's wrong here
Trigram indexes support similarity search but not full-text ranking.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Similar concept trap
Trigram indexes support similarity search but not full-text ranking.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which PCDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
- →
Design and implement database schemas — study guide chapter
Learn the concepts, then practise the questions
- →
Design and implement database schemas practice questions
Targeted practice on this topic area only
- →
All PCDE questions
503 questions across all exam domains
- →
Google Professional Cloud Database Engineer study guide
Full concept coverage aligned to exam objectives
- →
PCDE practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related PCDE practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Plan and manage database infrastructure practice questions
Practise PCDE questions linked to Plan and manage database infrastructure.
Define data structures and implement SQL for Business Intelligence practice questions
Practise PCDE questions linked to Define data structures and implement SQL for Business Intelligence.
Design and implement database schemas practice questions
Practise PCDE questions linked to Design and implement database schemas.
Monitor and optimize database performance practice questions
Practise PCDE questions linked to Monitor and optimize database performance.
PCDE fundamentals practice questions
Practise PCDE questions linked to PCDE fundamentals.
PCDE scenario practice questions
Practise PCDE questions linked to PCDE scenario.
PCDE troubleshooting practice questions
Practise PCDE questions linked to PCDE troubleshooting.
Practice this exam
Start a free PCDE practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this PCDE question test?
Design and implement database schemas — This question tests Design and implement database schemas — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a tsvector column with a GIN index on that column — Option A is correct: use a tsvector column with a GIN index, which is PostgreSQL's built-in full-text search feature optimized for ranking and relevance. Option B uses LIKE with wildcards, which is slow and cannot rank. Option C relies on an external service, not a schema design within Cloud SQL. Option D uses trigram indexes, which support similarity search but not full-text search ranking.
What should I do if I get this PCDE question wrong?
Identify which PCDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More PCDE practice questions
- A company stores sensor data in BigQuery. They have a table 'sensor_readings' with columns: sensor_id, reading_time, val…
- Which THREE are valid considerations when designing BigQuery tables for BI reporting?
- A team is migrating an on-premises PostgreSQL database to Cloud SQL for PostgreSQL. The existing schema uses a large num…
- A company is designing a Cloud Firestore schema for a social media application. Users can follow other users, and the ap…
- Match each Cloud SQL tier to its description.
- A financial services company uses Cloud Spanner for a global transaction processing system. They notice that certain rea…
Last reviewed: Jun 24, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.