Google Cloud Digital LeaderData and AI with Google CloudHard
A manufacturing company uses sensors on its assembly line to monitor equipment performance and predict potential failures. These sensors generate a continuous stream of time-series data at high velocity. The company needs a highly scalable, low-latency database specifically designed for storing and querying this time-series data efficiently. Which Google Cloud database is best suited for this use case?
- ACloud Bigtable
- BFirestore
- CCloud Spanner
- DCloud SQL
Show answer & explanationAnswer & explanation
Correct answer: A. Cloud Bigtable
Cloud Bigtable is a petabyte-scale, fully managed NoSQL wide-column database service, specifically optimized for large analytical and operational workloads, including time-series data, IoT, and operational analytics, offering high throughput and low latency.
Why the other options are wrong
- B. Firestore is a document database, suitable for flexible document storage, but Bigtable is superior for massive-scale time-series data with high throughput requirements.
- C. Cloud Spanner is a globally distributed relational database, but Bigtable is better optimized for the specific characteristics of time-series data (high write/read throughput, wide-column).
- D. Cloud SQL is a relational database, not designed for the high-volume, low-latency time-series data at petabyte scale.
Cloud Bigtable
A fully managed, scalable NoSQL wide-column database service designed for large analytical and operational workloads, including time-series data.
- Petabyte-scale, high throughput, low latency
- Ideal for time-series data, IoT, financial data, operational analytics
- Compatible with HBase API
Memory trick: Big data needs a Bigtable for time-series insights.