The answer is Cloud Bigtable. This is the correct choice because Bigtable is a fully managed, scalable NoSQL database engineered for high-throughput, low-latency writes, making it ideal for time-series sensor data from millions of globally distributed devices. Its architecture supports millions of writes per second by automatically sharding data across a cluster of nodes, and it provides high availability through built-in replication across zones. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of workload characteristics—specifically, that Bigtable excels at handling small, high-velocity writes with a device ID and timestamp as the row key, while Cloud Spanner or Firestore would be overkill or misaligned for pure time-series ingestion. A common trap is choosing Cloud SQL for its familiarity, but relational databases cannot match Bigtable’s write throughput at this scale. Memory tip: think “Bigtable for big writes”—if your sensor data is a firehose of tiny records, Bigtable is the hose.
PCDE Plan and manage database infrastructure Practice Question
This PCDE practice question tests your understanding of plan and manage database infrastructure. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 collects sensor data from millions of devices globally. Each write is a small record with a device ID and timestamp. They need low write latency and high availability. Which database should they choose?
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 with high throughput and low latency. It supports millions of writes per second from globally distributed devices, provides high availability through replication, and is optimized for time-series data like sensor records with device IDs and timestamps.
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 Firestore
Why it's wrong here
Firestore is suited for mobile and web apps, not high-throughput sensor data ingestion.
✗
Cloud Memorystore
Why it's wrong here
Memorystore is a caching layer, not a durable database for sensor data.
✗
Cloud SQL for MySQL
Why it's wrong here
Cloud SQL is not designed for millions of writes per second from global devices; limited scalability.
✓
Cloud Bigtable
Why this is correct
Bigtable excels at high write throughput, low latency, and is ideal for IoT time-series data.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that any NoSQL database is suitable for high-throughput writes, but candidates must distinguish between document stores (Firestore) and wide-column stores (Bigtable) designed for massive write scalability.
Detailed technical explanation
How to think about this question
Cloud Bigtable uses a distributed, sharded architecture based on Google's Chubby lock service and SSTables, enabling automatic sharding and load balancing for high write throughput. It supports HBase API compatibility, allowing integration with big data ecosystems like Apache Spark and Hadoop. In real-world IoT deployments, Bigtable can handle over 1 million writes per second per table with sub-10ms latency, making it ideal for time-series sensor data.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
Plan and manage database infrastructure — This question tests Plan and manage database infrastructure — 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 with high throughput and low latency. It supports millions of writes per second from globally distributed devices, provides high availability through replication, and is optimized for time-series data like sensor records with device IDs and timestamps.
What should I do if I get this PCDE 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 →
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. A company needs to store time-series sensor data with high write throughput (millions of writes per second) and low latency reads. Which database service should they choose?
easy
✓ A.Cloud Bigtable
B.Cloud SQL
C.Firestore
D.Cloud Spanner
Why A: Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, handling millions of writes per second with consistent low-latency reads. It uses a distributed, replicated SSTable storage engine and is optimized for time-series data, making it ideal for high-throughput sensor ingestion.
Last reviewed: Jun 30, 2026
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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.
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