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A data analytics company processes large volumes of streaming data from IoT devices. They need a highly scalable, fully managed service to ingest and process this data in real-time before storing it in BigQuery for further analysis. The solution must support high throughput and low latency. Which Google Cloud service should they use for data ingestion and real-time processing?

  1. ACloud Dataflow
  2. BCloud Pub/Sub
  3. CCloud SQL
  4. DCloud Storage
Show answer & explanation

Correct answer: B. Cloud Pub/Sub

Cloud Pub/Sub is a fully managed, real-time messaging service designed for high-throughput, low-latency data ingestion from streaming sources like IoT devices, making it ideal for this scenario.

Why the other options are wrong

  • A. Cloud Dataflow is a data processing service, often used with Pub/Sub for stream processing, but Pub/Sub is for ingestion.
  • C. Cloud SQL is a relational database service, not suitable for high-throughput real-time streaming data ingestion.
  • D. Cloud Storage is an object storage service, not designed for real-time streaming data ingestion and processing.

Cloud Pub/Sub

A fully managed, real-time messaging service that enables asynchronous communication between applications and services, ideal for streaming data ingestion.

  • Scalable to petabytes of data.
  • Low-latency message delivery.
  • Decouples senders and receivers.
  • Supports push and pull subscriptions.

Memory trick: Publish and Subscribe to the stream, that's Pub/Sub's scheme.

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