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Explain Streams and Tasks in Snowflake.

SQLeasy0.4 min read

**Architectural Logic**: Streams = CDC; Tasks = scheduled SQL; together enable near-real-time ELT. **Streams**: Capture INSERT/UPDATE/DELETE from table; query stream for changed rows. **Tasks**: Scheduled SQL; can be triggered by stream data. **Pattern**: `CREATE STREAM s ON...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Cognizant
Key Concepts Tested
snowflakesql

Why This Question Matters

This easy-level SQL question appears frequently in data engineering interviews at companies like Cognizant. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (snowflake, sql) will help you answer variations of this question confidently.

How to Approach This

Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
88 words

Architectural Logic: Streams = CDC; Tasks = scheduled SQL; together enable near-real-time ELT. Streams: Capture INSERT/UPDATE/DELETE from table; query stream for changed rows. Tasks: Scheduled SQL; can be triggered by stream data. Pattern: CREATE STREAM s ON TABLE t; CREATE TASK process SCHEDULE='1 minute' WHEN SYSTEM$STREAM_HAS_DATA('s') AS INSERT INTO target SELECT * FROM s. Use: Incremental processing; CDC pipelines. Scalability: Stream lag monitoring; task error notifications. Cost: Stream storage; task compute. Best Practice: Streams for change tracking; tasks for automation; combine for near-real-time; simpler than external CDC tools.

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