Microsoft Certified: Azure Solutions Architect ExpertDesign data storage solutionsHard
A research institution is collecting sensor data from various environmental monitoring stations. This data consists of time-series readings (temperature, humidity, pressure) generated every minute. The institution needs to store this data efficiently for long-term retention (decades) and perform aggregate queries over specific time ranges (e.g., average temperature for a month, maximum pressure for a week). The data is append-only, and individual record updates are rare. Which Azure non-relational data storage solution is most appropriate?
- AAzure Time Series Insights
- BAzure Cosmos DB
- CAzure SQL Database
- DAzure Table Storage
Show answer & explanationAnswer & explanation
Correct answer: A. Azure Time Series Insights
Azure Time Series Insights is a fully managed analytics, storage, and visualization service optimized for industrial IoT deployments. It's purpose-built for storing, analyzing, and querying large volumes of time-series data efficiently, supporting long-term retention and fast aggregate queries over time ranges, which perfectly fits the sensor data scenario.
Why the other options are wrong
- B. Azure Cosmos DB can store time-series data, but it's a general-purpose NoSQL database. Azure Time Series Insights is specifically optimized for time-series data with built-in analytical capabilities.
- C. Azure SQL Database is a relational database and not optimized for the specific characteristics and query patterns of time-series data at scale.
- D. Azure Table Storage is a key-value store, not optimized for complex time-series queries and aggregations across long time spans.
Azure Time Series Insights
A fully managed analytics, storage, and visualization service for industrial IoT. It's optimized for collecting, processing, storing, and querying large volumes of time-series data generated by IoT devices and sensors.
- Purpose-built for time-series data
- Efficient storage and long-term retention
- Fast aggregate queries over time ranges
- Integrates with IoT Hub and Event Hubs
Memory trick: Time Series Insights finds trends in your time-stamped data, like a historian.