- A
Bigtable
Why wrong: Bigtable provides eventual consistency, not strong global consistency, and does not support complex analytical queries in SQL. It is optimized for real-time analytics on time-series data, not transactional workloads.
- B
AlloyDB
Why wrong: AlloyDB offers high write throughput and HTAP (columnar engine for analytics), but its cross-region replication using AlloyDB Omni is eventually consistent, failing the strong global consistency requirement.
- C
BigQuery
Why wrong: BigQuery is a data warehouse for analytical queries, not a transactional database. It cannot provide strong global consistency for writes or high write throughput for OLTP workloads.
- D
Firestore
Why wrong: Firestore provides strong consistency only within a single region; multi-region is eventually consistent. It does not support complex analytical queries and has lower write throughput for transactional applications.
- E
Cloud Spanner
Cloud Spanner meets all three: strong global consistency via synchronous multi-region replication, high write throughput (scalable), and support for transactional workloads. It does not natively run complex analytical queries, but that can be addressed with external analytics tools.
PCDOE Strong global consistency Practice Question
This PCDOE practice question tests your understanding of design and plan database solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. A key principle to apply: strong global consistency. 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 is evaluating Google Cloud databases for a new application that requires: (1) strong global consistency across multiple regions, (2) the ability to run complex analytical queries on the same data as the transactional workload, and (3) high write throughput. Which TWO databases should they consider?
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 Spanner
Cloud Spanner provides strong global consistency across multiple regions via multi-region configurations using synchronous replication, high write throughput (up to 20,000 writes per second per node, scalable), and support for transactional workloads. However, it does not natively handle complex analytical queries on the same data; for HTAP, a separate analytics engine like BigQuery or a dedicated HTAP database such as AlloyDB would be needed. AlloyDB offers HTAP and high write throughput, but its cross-region replication is eventually consistent, failing the strong global consistency requirement. BigQuery lacks transactional strong consistency and high write throughput. Bigtable provides eventual consistency and no SQL analytical queries. Firestore offers strong consistency only within a single region and no complex analytical queries. Thus, only Cloud Spanner fully meets the three requirements.
Key principle: Strong global consistency
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Bigtable
Why it's wrong here
Bigtable provides eventual consistency, not strong global consistency, and does not support complex analytical queries in SQL. It is optimized for real-time analytics on time-series data, not transactional workloads.
- ✗
AlloyDB
Why it's wrong here
AlloyDB offers high write throughput and HTAP (columnar engine for analytics), but its cross-region replication using AlloyDB Omni is eventually consistent, failing the strong global consistency requirement.
- ✗
BigQuery
Why it's wrong here
BigQuery is a data warehouse for analytical queries, not a transactional database. It cannot provide strong global consistency for writes or high write throughput for OLTP workloads.
- ✗
Firestore
Why it's wrong here
Firestore provides strong consistency only within a single region; multi-region is eventually consistent. It does not support complex analytical queries and has lower write throughput for transactional applications.
- ✓
Cloud Spanner
Why this is correct
Cloud Spanner meets all three: strong global consistency via synchronous multi-region replication, high write throughput (scalable), and support for transactional workloads. It does not natively run complex analytical queries, but that can be addressed with external analytics tools.
Related concept
Strong global consistency
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often assume AlloyDB provides strong global consistency because of its marketing around 'global scale' and 'cross-region replication', but in reality its cross-region replication is eventually consistent. Cloud Spanner is the only Google Cloud database offering strong global consistency across multiple regions.
Detailed technical explanation
How to think about this question
AlloyDB's columnar engine automatically offloads analytical queries from the transactional engine, enabling HTAP without ETL; it uses a PostgreSQL-compatible interface and leverages Google's distributed storage architecture to achieve up to 4x faster analytical queries than standard PostgreSQL. Under the hood, AlloyDB separates compute from storage, allowing independent scaling of read replicas and write nodes, and its cross-region replication uses synchronous replication for strong consistency, with a recovery point objective (RPO) of zero.
KKey Concepts to Remember
- Strong global consistency
- HTAP (Hybrid Transactional/Analytical Processing)
- High write throughput
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
Strong global consistency
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. Strong global consistency Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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What to study next
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FAQ
Questions learners often ask
What does this PCDOE question test?
Design and Plan Database Solutions — This question tests Design and Plan Database Solutions — Strong global consistency.
What is the correct answer to this question?
The correct answer is: Cloud Spanner — Cloud Spanner provides strong global consistency across multiple regions via multi-region configurations using synchronous replication, high write throughput (up to 20,000 writes per second per node, scalable), and support for transactional workloads. However, it does not natively handle complex analytical queries on the same data; for HTAP, a separate analytics engine like BigQuery or a dedicated HTAP database such as AlloyDB would be needed. AlloyDB offers HTAP and high write throughput, but its cross-region replication is eventually consistent, failing the strong global consistency requirement. BigQuery lacks transactional strong consistency and high write throughput. Bigtable provides eventual consistency and no SQL analytical queries. Firestore offers strong consistency only within a single region and no complex analytical queries. Thus, only Cloud Spanner fully meets the three requirements.
What should I do if I get this PCDOE question wrong?
Review strong global consistency, then practise related PCDOE questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Strong global consistency
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Last reviewed: Jul 4, 2026
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