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A consulting firm is designing a new solution for a client that involves processing large datasets (petabytes) of historical sales data, customer interactions, and sensor readings for advanced analytics and machine learning. The data needs to be stored in its raw format, support hierarchical namespaces, and be optimized for analytical workloads. Which Azure storage solution should be recommended?
- AAzure Cosmos DB
- BAzure Data Lake Storage Gen2
- CAzure SQL Database
- DAzure Blob Storage (Standard)
Show answer & explanationAnswer & explanation
Correct answer: B. Azure Data Lake Storage Gen2
Azure Data Lake Storage Gen2 is purpose-built for big data analytics. It combines the scalability and cost-effectiveness of Azure Blob Storage with a hierarchical file system, making it optimized for petabyte-scale data, supporting raw data formats, and compatible with various analytics engines like Azure Synapse Analytics and Azure Databricks.
Why the other options are wrong
- A. Azure Cosmos DB is a NoSQL database, suitable for transactional workloads and specific semi-structured data, but not the primary choice for petabyte-scale raw data storage for data lake analytics.
- C. Azure SQL Database is a relational database and is not designed for storing petabytes of raw, unstructured or semi-structured data for big data analytics.
- D. Azure Blob Storage (Standard) can store large amounts of data, but it lacks the hierarchical namespace and deep optimization for analytical workloads that Data Lake Storage Gen2 provides.
Azure Data Lake Storage Gen2
A set of capabilities dedicated to big data analytics, built on Azure Blob Storage, that provides a hierarchical file system.
- Optimized for big data analytics workloads.
- Supports petabyte-scale storage and beyond.
- Provides a hierarchical namespace for file system semantics.
Memory trick: Data Lake Gen2: A 'Lake' of 'Data' for next 'Gen' analytics.