Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Types of views: (1) Standard view—virtual table, query stored; data fetched at query time. (2) Materialized view—physical storage; pre-computed results; faster reads, needs refresh. (3) Indexed view (SQL Server)—materialized with indexes. (4) Secure view (Snowflake)—hides...
Types of views: (1) Standard view—virtual table, query stored; data fetched at query time. (2) Materialized view—physical storage; pre-computed results; faster reads, needs refresh. (3) Indexed view (SQL Server)—materialized with indexes. (4) Secure view (Snowflake)—hides underlying data from unauthorized users. Use standard views for abstraction; materialized for performance. Trade-off: Materialized views have storage and refresh cost. Best practice: Use materialized views for heavy aggregations; incremental refresh when supported. 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.'
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.