PDE Storing the Data Practice Question
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?
⚠ Common exam trap
A common trap in Google Cloud exams is confusing operational databases (Bigtable) with analytical warehouses (BigQuery). The petabyte-scale data might suggest BigQuery, but the single-digit millisecond latency and high throughput key-value access pattern require Bigtable's purpose-built design.
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 sub-10ms latency at millions of reads per second. Its key-value model with timestamps directly matches the time-series IoT sensor data structure, and it supports high-throughput, low-latency access via the HBase API or Bigtable client libraries.
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
Cloud Bigtable is a wide-column NoSQL store built on a sparse sorted map, delivering consistent single-digit millisecond latency at millions of reads per second. Its row-key design suits timestamped key-value IoT data at petabyte scale, matching every stated constraint.
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BigQuery
Why it's wrong here
BigQuery is an analytics warehouse optimised for large scans and aggregations, not single-digit millisecond point reads at millions per second. It tempts because it genuinely handles petabyte-scale time-series storage and SQL querying, making it the right choice for batch analytics and dashboards rather than low-latency key lookups.
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Cloud Spanner
Why it's wrong here
Cloud Spanner is a strongly consistent, horizontally scalable relational database with SQL and transactions, not a key-value store; its latency cannot sustain millions of reads per second on simple timestamped keys. It tempts when global transactional consistency is required, such as multi-region financial ledgers, but that is not this workload.
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Firestore
Why it's wrong here
Firestore is a document database with per-document consistency and limited write throughput, so it cannot serve millions of key-value reads per second at single-digit millisecond latency across petabytes. It tempts for mobile and web app synchronisation with real-time listeners, not high-volume IoT time-series ingestion.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.