CLOUD-DIGITAL-LEADER · Question #61
A fitness band company is continuously ingesting data from millions of its consumers. Different kinds of data based on time, like location, heartbeat rate, temperature, movement, etc. are…
The correct answer is B. Bigtable. Cloud Bigtable is the ideal choice for this fitness band IoT scenario. It is a fully managed, high-throughput, low-latency NoSQL wide-column database optimized for time-series data (exactly what fitness metrics like heartbeat, temperature, and location represent). It supports…
Question
A fitness band company is continuously ingesting data from millions of its consumers. Different kinds of data based on time, like location, heartbeat rate, temperature, movement, etc. are connect-ed. They need a high throughput database that can write data very fast. Since their users are spread across the world, they need the database to be geographically scalable. Consumers also want to see near-real-time visualizations of their activities. Which of these databases would be a good fit?
Options
- ACloud SQL
- BBigtable
- CSpanner
- DFirestore
How the community answered
(30 responses)- A7% (2)
- B73% (22)
- C7% (2)
- D13% (4)
Explanation
Cloud Bigtable is the ideal choice for this fitness band IoT scenario. It is a fully managed, high-throughput, low-latency NoSQL wide-column database optimized for time-series data (exactly what fitness metrics like heartbeat, temperature, and location represent). It supports petabyte-scale storage, global replication for geographic scalability, and handles millions of reads/writes per second. Cloud SQL (A) is a relational database not designed for massive IoT ingestion at this scale. Cloud Spanner (C) is a globally-distributed relational database suited for transactional workloads, not high-speed time-series ingestion. Cloud Firestore (D) is a document database better suited for mobile/web app data, not high-throughput sensor streams.
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