Select Two (Multi-Select) Questions

Azure SQL Database Single Database

Why wrong: Single Database does not support SQL Agent or Service Broker, and its resource allocation is per database, not suited for high CPU/memory needs.

Azure SQL Database Elastic Pool

Why wrong: Elastic Pool is for pooling resources across multiple databases; it does not support SQL Agent or Service Broker and is not intended for a single high-resource workload.

Consistency (C) and Partition Tolerance (P)

Why wrong: Choosing Consistency and Partition Tolerance would mean that during a network partition, the system cannot guarantee availability (e.g., it might refuse writes or reads from some regions to maintain consistency). This is not what the scenario describes—the system must keep accepting bids.

Consistency (C) and Availability (A)

Why wrong: According to the CAP theorem, it is impossible to guarantee both Consistency and Availability in the presence of a network partition. The system must tolerate partitions, so this combination is not achievable in practice.

Azure SQL Database

Why wrong: Azure SQL Database is a relational database for structured data.

Azure Table Storage

Why wrong: Azure Table Storage is a key-value store for structured NoSQL data.

Azure Cosmos DB

Why wrong: Azure Cosmos DB is a NoSQL database for semi-structured data.

Normalized data storage

Why wrong: Normalization is a relational database practice, not typical for NoSQL.

Strong ACID transaction support

Why wrong: Many NoSQL databases sacrifice ACID for performance and scalability.

Relational data model

Why wrong: NoSQL databases use non-relational models.

Enforced referential integrity constraints

Why wrong: Referential integrity is a relational concept, not a feature of storage formats.

Optimized for frequent row updates

Why wrong: Columnar formats are not efficient for row-level updates; they are designed for read-heavy analytics.

Cost per GB

Why wrong: Cost is generally a consideration but not a key differentiator; both have different pricing models.

Maximum data size

Why wrong: Both can handle large data sizes; not a deciding factor.

Azure SQL Database

Why wrong: Relational database for structured data.

Azure Data Lake Storage

Why wrong: Optimized for unstructured big data.

Azure Blob Storage

Why wrong: Blob Storage is a storage service, not a transformation service.

Azure SQL Database

Why wrong: SQL Database is a relational database; transformation can be done via stored procedures but not as a primary pipeline transformation service.

Azure Event Hubs

Why wrong: Event Hubs is for data ingestion, not transformation.

Azure Synapse Analytics dedicated SQL pool

Why wrong: Synapse SQL pool is also PaaS, but we need exactly two; select B and D.

Azure Data Lake Storage Gen2

Why wrong: Data Lake Storage is a storage service (PaaS), but the question expects exactly two; we choose B and D as the most typical PaaS data stores.

Azure Virtual Machines with SQL Server

Why wrong: Virtual Machines are IaaS; you manage the OS and software.

Azure Cosmos DB

Why wrong: Stores semi-structured data (JSON documents).

Azure Data Lake Storage

Why wrong: Stores unstructured or semi-structured data in files.

Azure Blob Storage

Why wrong: Stores unstructured data like files and images.

Support for complex joins

Why wrong: Relational databases are better for joins.

ACID transactions across multiple records

Why wrong: Relational databases are stronger in ACID.

Enforced referential integrity

Why wrong: Relational databases enforce referential integrity.

Data uses tags or markers to separate elements

Why wrong: This describes semi-structured data like JSON.

Data is stored in Azure Cosmos DB

Why wrong: Cosmos DB stores semi-structured data, not exclusively structured.

Data has no predefined schema

Why wrong: This describes unstructured data.

Azure Databricks with Apache Spark

Why wrong: Typically requires cluster management, though serverless options exist.

Azure SQL Database

Why wrong: Provisioned database, not serverless transformation.

Azure HDInsight with Hive

Why wrong: Requires cluster management.

Stores unstructured data like videos

Why wrong: Data warehouses are for structured/relational data.

Enables real-time streaming analytics

Why wrong: Data warehouses are not built for real-time streaming.

Azure Data Explorer

Why wrong: Interactive analytics on time-series data.

Azure Stream Analytics

Why wrong: Real-time stream processing.

Azure Analysis Services

Why wrong: OLAP modeling.

Azure Stream Analytics

Why wrong: Real-time stream processing, not a core component of batch data warehouse.

Azure Cosmos DB

Why wrong: NoSQL database for operational workloads, not typical for data warehousing.

Azure Blob Storage

Why wrong: Blob Storage is for storage, not stream processing.

Azure Data Factory

Why wrong: Data Factory is for orchestration, not real-time stream processing.

Azure Synapse Analytics

Why wrong: Synapse is a serving layer and analytics platform, not a stream processing engine.

Power BI

Why wrong: Used for analytics, not data ingestion.

Azure SQL Database

Why wrong: It's a data source, not an ingestion method.

Azure DevOps

Why wrong: Focused on application lifecycle, not data ingestion.

Azure Data Lake Storage

Why wrong: Data Lake is for batch storage, not real-time.

Azure Analysis Services

Why wrong: Analysis Services is for semantic models, not real-time.

Power BI

Why wrong: Visualization tool, not part of data warehouse architecture.

Azure Stream Analytics

Why wrong: Real-time analytics, not core to modern data warehouse.