A company is collecting data from several thousand machines globally. Which software component in the overall architecture is the next destination of the dataflow after the data has been gathered…

Question

Options

• Arelational database: MySQL
• Bhistorian database: influxDB
• Cmessage broker: Apache Kafka
• Ddashboard: Node.js web app

• A
  5% (3)
• B
  80% (48)
• C
  12% (7)
• D
  3% (2)

Explanation

After edge software gathers and normalizes machine data, a historian database like InfluxDB is the correct next destination because it is purpose-built for high-volume, time-series industrial data ingestion - exactly what thousands of machines produce continuously. InfluxDB acts as the persistent storage layer, efficiently recording timestamped sensor readings at scale before any further processing or visualization occurs.

Why the distractors are wrong:

• A (MySQL): Relational databases are optimized for structured, transactional records - not the high-frequency, append-heavy time-series writes produced by machine telemetry. They would become a bottleneck.
• C (Apache Kafka): Kafka is a transport layer (message broker), not a destination. It moves data between systems; it doesn't store it long-term. In architectures that include Kafka, it typically sits before the historian, not after the edge.
• D (Node.js dashboard): Dashboards are consumers at the end of the pipeline - they read from a database; they cannot receive or store raw normalized data.

Memory tip: Think of the historian as the "recorder" - just like a flight data recorder captures everything in sequence, InfluxDB records all the normalized machine data in time order, so dashboards and analytics can query it later. Edge normalizes → Historian stores → Dashboard displays.

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