Quick Answer
The answer is Azure Blob Storage and Azure Synapse Analytics. These are both valid output sinks for Azure Stream Analytics because the service natively supports writing real-time streaming data to Blob Storage for cost-effective, unstructured data lake storage, and to Synapse Analytics dedicated SQL pools via the built-in PolyBase or COPY INTO adapters for high-performance analytical queries. On the Microsoft Azure Data Engineer Associate DP-203 exam, this concept tests your understanding of Stream Analytics output options, often appearing in scenario-based questions where you must choose sinks that support both batch and interactive analytics. A common trap is confusing Azure SQL Database (which is also valid) with Synapse Analytics, but the exam specifically highlights Synapse for large-scale data warehousing. Memory tip: think “Blob for bulk, Synapse for speed” — both are native, high-throughput sinks that avoid custom code.
This DP-203 practice question tests your understanding of develop data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are using Azure Stream Analytics to process real-time data from an Event Hub. Which TWO of the following are valid output sinks?
Azure Synapse Analytics
Supported via a dedicated SQL pool.
Azure Blob Storage
Supported for batch writes.
Azure Queue Storage
Why wrong: Not a supported output.
Azure Files
Why wrong: Not a supported output sink.
Azure Table Storage
Why wrong: Not directly supported; Cosmos DB Table API is supported.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Azure Synapse Analytics
Azure Stream Analytics supports Azure Synapse Analytics as a native output sink, allowing you to write real-time streaming results directly into dedicated SQL pools for high-performance analytics. This is achieved via the built-in Azure Synapse Analytics output adapter, which uses PolyBase or COPY INTO for efficient bulk ingestion.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure Synapse Analytics
Why this is correct
Supported via a dedicated SQL pool.
Related concept
Read the scenario before looking for a memorised answer.
Azure Blob Storage
Why this is correct
Supported for batch writes.
Related concept
Read the scenario before looking for a memorised answer.
Azure Queue Storage
Why it's wrong here
Not a supported output.
Azure Files
Why it's wrong here
Not a supported output sink.
Azure Table Storage
Why it's wrong here
Not directly supported; Cosmos DB Table API is supported.
Common exam traps
The trap here is that candidates often confuse Azure Table Storage or Queue Storage as valid sinks because they are general Azure storage services, but Stream Analytics has a specific, limited set of supported output sinks documented in official Microsoft documentation.
Trap categories for this question
Command / output trap
Not a supported output.
Detailed technical explanation
Azure Stream Analytics uses a job-defined query to process events from inputs like Event Hubs and then routes results to outputs via built-in adapters. For Azure Synapse Analytics, the adapter leverages PolyBase to stage data in Azure Blob Storage before loading into the SQL pool, ensuring high-throughput writes. In real-world scenarios, this is critical for near-real-time dashboards where latency must be under seconds, and the adapter handles partitioning and retries automatically to maintain exactly-once delivery semantics.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Develop data processing — This question tests Develop data processing — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Synapse Analytics — Azure Stream Analytics supports Azure Synapse Analytics as a native output sink, allowing you to write real-time streaming results directly into dedicated SQL pools for high-performance analytics. This is achieved via the built-in Azure Synapse Analytics output adapter, which uses PolyBase or COPY INTO for efficient bulk ingestion.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.
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