Microsoft Azure Data FundamentalsDescribe how to work with non-relational data on AzureHard
A company is building an application that needs to store IoT device telemetry data. This data consists of simple, structured records (e.g., device ID, timestamp, temperature, humidity) that are frequently written and occasionally queried by device ID or timestamp range. The company requires a highly scalable, low-cost solution for storing billions of these entities, where global distribution and advanced querying capabilities (like joins or aggregations) are not a primary concern. Which Azure non-relational data service is the most appropriate?
- AAzure Table Storage
- BAzure Data Lake Storage Gen2
- CAzure Blob Storage (Hot tier)
- DAzure Cosmos DB (SQL API)
Show answer & explanationAnswer & explanation
Correct answer: A. Azure Table Storage
Azure Table Storage is a NoSQL key-value store optimized for storing large amounts of structured, non-relational data. It offers high scalability and low cost, making it ideal for billions of simple entities like IoT telemetry where complex querying or global distribution of a full Cosmos DB account isn't required. Its design allows for efficient lookups by PartitionKey and RowKey.
Why the other options are wrong
- B. Azure Data Lake Storage Gen2 is for big data analytics and large files, not optimized for storing and querying billions of small, structured entities in a key-value fashion.
- C. Azure Blob Storage is for unstructured object storage, not a database service for structured key-value entities with query requirements.
- D. Azure Cosmos DB (SQL API) offers more advanced features like global distribution and richer querying, which would be an overkill and more expensive if not fully utilized for this simple, structured data.
Azure Table Storage
A NoSQL key-value store service that stores large amounts of structured, non-relational data. It is a highly scalable and cost-effective solution for applications requiring flexible data models and fast access.
- Stores entities (rows) in tables.
- Each entity has a PartitionKey and a RowKey for unique identification.
- Offers schema-less design for flexible attributes.
- Highly scalable and cost-effective for large volumes of simple, structured data.
Memory trick: Table Storage is like a 'simple spreadsheet' for your data, efficient and cheap.