Design innovative, scalable, and highly available cloud database solutions →mediumMultiple ChoiceObjective-mapped
PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A company is migrating a large on-premise Hadoop workload to Google Cloud. The data is stored in HBase and consists of time-series logs with 10 PB of data. They need a fully managed NoSQL solution with high throughput and low latency. Which migration path should they choose?
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
✓
Use Cloud Bigtable and the HBase client
Cloud Bigtable is the fully managed, scalable NoSQL database that is compatible with HBase API, making migration straightforward. Cloud Spanner is relational, not the best for time-series logs. BigQuery is for analytics, not real-time. Firestore is document-based and not suited for petabyte-scale logs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Migrate HBase tables to Cloud Spanner using Dataflow
Why it's wrong here
Spanner is relational and overkill for time-series; HBase to Spanner migration is complex.
- ✗
Export data to BigQuery using Storage Transfer Service
Why it's wrong here
BigQuery is an analytics data warehouse, not a real-time database.
- ✗
Re-architect as Firestore collections
Why it's wrong here
Firestore is not designed for petabyte-scale time-series data.
- ✓
Use Cloud Bigtable and the HBase client
Why this is correct
Bigtable supports HBase client via the Bigtable HBase client, allowing a smooth migration.
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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.