- A
Cloud Bigtable
Bigtable is the correct choice: wide-column NoSQL, designed for time-series and IoT workloads, single-digit ms latency, and scales to millions of QPS with additional nodes.
- B
Cloud Spanner
Why wrong: Spanner is a globally distributed relational database optimised for ACID transactions, not single-digit ms time-series reads at millions of QPS.
- C
Firestore
Why wrong: Firestore is a document database suited for mobile/web apps with hierarchical data. It does not scale to millions of QPS for time-series workloads.
- D
BigQuery
Why wrong: BigQuery is an analytics data warehouse with query latency measured in seconds. It is not designed for millisecond lookups at IoT scale.
Question 271 of 980
PCD Practice Question: Manage a Solution that Can Span Multiple Database Systems
This PCD practice question tests your understanding of manage a solution that can span multiple database systems. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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.
A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database 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
✓
Cloud Bigtable
Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, handling petabytes of data with consistent single-digit millisecond latency at high throughput. Its key-value and wide-column architecture, combined with native time-series optimization via row key design (e.g., inverted timestamps), makes it the ideal choice for IoT sensor data requiring millions of reads per second.
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.
- ✓
Cloud Bigtable
Why this is correct
Bigtable is the correct choice: wide-column NoSQL, designed for time-series and IoT workloads, single-digit ms latency, and scales to millions of QPS with additional nodes.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Cloud Spanner
Why it's wrong here
Spanner is a globally distributed relational database optimised for ACID transactions, not single-digit ms time-series reads at millions of QPS.
- ✗
Firestore
Why it's wrong here
Firestore is a document database suited for mobile/web apps with hierarchical data. It does not scale to millions of QPS for time-series workloads.
- ✗
BigQuery
Why it's wrong here
BigQuery is an analytics data warehouse with query latency measured in seconds. It is not designed for millisecond lookups at IoT scale.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that Cloud Spanner is the universal solution for any high-throughput database need, but candidates must recognize that Spanner's relational model and global consistency overhead make it unsuitable for simple key-value time-series workloads at petabyte scale with millions of reads per second.
Detailed technical explanation
How to think about this question
Cloud Bigtable uses a distributed, sharded storage architecture based on Google's Chubby and GFS, where data is partitioned into tablets and served by tablet servers; row keys are lexicographically sorted, so designing an inverted timestamp (e.g., `[sensor_id]#[MAX_TIMESTAMP - timestamp]`) enables efficient range scans for recent data. Bigtable supports the HBase API and can achieve over 1 million queries per second per cluster with proper row key design, making it a common choice for ad-tech, financial tick data, and IoT telemetry.
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.
TExam Day Tips
- 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this PCD question test?
Manage a Solution that Can Span Multiple Database Systems — This question tests Manage a Solution that Can Span Multiple Database Systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Cloud Bigtable — Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, handling petabytes of data with consistent single-digit millisecond latency at high throughput. Its key-value and wide-column architecture, combined with native time-series optimization via row key design (e.g., inverted timestamps), makes it the ideal choice for IoT sensor data requiring millions of reads per second.
What should I do if I get this PCD question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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 →
Last reviewed: Jul 4, 2026
This PCD 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 PCD exam.
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