The original title is "Normalization vs. Denormalization: The Great Database Debate"

Short summary

Normalization eliminates data redundancy for write-heavy systems, while denormalization duplicates data for read speed in analytics. Most production systems combine both: keep operational databases normalized, transform them into denormalized data warehouses via ETL pipelines, and denormalize specific queries only when performance demands justify it.

• •Normalization optimizes for writes and data consistency; denormalization optimizes for read speed
• •Transactional systems benefit from normalization; analytical systems from denormalization
• •Hybrid approach: normalized operational DB + denormalized warehouse with ETL pipeline

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