Google Associate Cloud EngineerPlanning and configuring a cloud solutionMedium
A startup is deploying a new IoT platform that will ingest millions of small, high-throughput sensor readings per second. These readings need to be stored with very low latency for real-time dashboards and anomaly detection. The data is key-value based, non-relational, and will grow to petabytes over time. Which Google Cloud database is best suited for this workload?
- ACloud Bigtable
- BCloud SQL
- CFirestore
- DCloud Spanner
Show answer & explanationAnswer & explanation
Correct answer: A. Cloud Bigtable
Cloud Bigtable is a fully managed, NoSQL wide-column database service ideal for analytical and operational workloads involving large amounts of single-digit millisecond latency data. It is designed for high throughput and scalability, making it perfect for IoT sensor data and real-time applications.
Why the other options are wrong
- B. Cloud SQL is a relational database not designed for the extremely high write throughput and petabyte scale of IoT sensor data.
- C. Firestore is a NoSQL document database suitable for mobile, web, and serverless applications, but it's not designed for the extreme ingest rates and petabyte scale of Bigtable for IoT.
- D. Cloud Spanner is a globally distributed relational database with strong consistency, but it's optimized for transactional workloads and would be overkill and more expensive for raw IoT sensor ingest.
Cloud Bigtable
A fully managed, scalable NoSQL wide-column database service for large analytical and operational workloads, offering high throughput and low latency for massive datasets.
- NoSQL wide-column store
- High throughput (millions of writes/second)
- Low latency (single-digit milliseconds)
- Petabyte-scale
- Ideal for IoT, time-series data, operational analytics
Memory trick: Bigtable is for big, fast tables; Firestore is for flexible documents.