Google ACE Planning and Configuring a Cloud Solution 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
ACE often tests the distinction between Bigtable and BigQuery for time-series data: candidates may choose BigQuery for its scalability, but BigQuery is not designed for single-digit millisecond latency at millions of reads per second; Bigtable is the correct choice for high-throughput, low-latency key-value access.
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, high-performance NoSQL wide-column database designed for massive analytical and operational workloads. It excels at storing petabytes of data and delivering single-digit millisecond latency for high-throughput reads/writes (millions of ops/sec) when using row-key based access. Its sparse table design and automatic sharding make it ideal for time-series IoT data where the row key can incorporate a timestamp for efficient range scans.
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 sparse, wide-column NoSQL store engineered for petabyte-scale time-series workloads, delivering consistent single-digit millisecond latency and linear horizontal scaling to millions of reads per second. Its row-key design suits the simple key-value timestamp structure, satisfying the stem's throughput and latency constraints.
- ✗
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 cannot meet that latency profile. It is tempting because it stores petabytes cheaply and handles time-series analytics well, but Bigtable is the correct choice for high-throughput key-value lookups.
- ✗
Firestore
Why it's wrong here
Firestore is a document database whose per-document read pricing and query model cannot sustain millions of reads per second at single-digit millisecond latency across petabytes. It fits mobile and web app backends needing real-time sync and offline support, not high-throughput time-series ingestion.
- ✗
Cloud Spanner
Why it's wrong here
Cloud Spanner is a globally distributed relational database with strong consistency, so its per-row transactional overhead cannot deliver single-digit millisecond reads at millions per second for simple key-value time-series data. It suits horizontally scalable OLTP workloads needing relational semantics and multi-region consistency, not this ingestion pattern.
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This ACE question is part of Courseiva's 775-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This ACE 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 ACE exam.