You are choosing a database backend for a new application. The application will ingest data points from IoT sensors. You need to ensure that the application can scale up to millions of requests per…

Question

Options

• AUse Cloud SQL with read replicas for throughput.
• BUse Firestore, and rely on automatic serverless scaling.
• CUse Memorystore for Memcached, and add nodes as necessary to achieve the required
• DUse Bigtable, and add nodes as necessary to achieve the required throughput.

• A
  3% (1)
• B
  8% (3)
• C
  13% (5)
• D
  77% (30)

Explanation

Bigtable is Google Cloud's managed NoSQL wide-column database purpose-built for high-throughput, low-latency workloads such as IoT time-series data ingestion. It scales horizontally by adding nodes, can handle millions of read/write operations per second, delivers single-digit millisecond latency, and supports petabyte-scale storage - well within the 100 TB requirement. Option A (Cloud SQL) is a relational database that cannot scale to millions of requests per second. Option B (Firestore) is a document database with automatic scaling but is not optimized for the volume and throughput of IoT sensor streams at this scale. Option C (Memorystore for Memcached) is an in-memory cache and cannot persistently store 100 TB of historical data.

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