Reviewed by Aditya Kumar · Last reviewed 2026-03-24
UNION combines results of two queries and removes duplicates (like DISTINCT). UNION ALL keeps all rows, including duplicates. UNION ALL is faster: no deduplication sort/hash. Use UNION when duplicates must be removed; UNION ALL when you know sources are disjoint or duplicates...
This medium-level SQL question appears frequently in data engineering interviews at companies like Aarete. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
UNION combines results of two queries and removes duplicates (like DISTINCT). UNION ALL keeps all rows, including duplicates. UNION ALL is faster: no deduplication sort/hash. Use UNION when duplicates must be removed; UNION ALL when you know sources are disjoint or duplicates are acceptable. Example: SELECT a FROM t1 UNION ALL SELECT a FROM t2. Best practice: Prefer UNION ALL unless dedup is required; it scales better and is clearer about intent. Why it matters: Design choices compound at scale—wrong approach can cause 100× overhead. Scalability trade-offs: Profile before optimizing; validate on sample then full. Cost implications: Suboptimal choices multiply at billion-row scale.
Red Flag: Generic textbook answers. Pro-Move: 'At scale we measured X, implemented Y, achieved Z%—validated and iterated.'
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According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.