OLTP vs OLAP: Transactional vs Analytical Workloads
~10 min read
Why a data warehouse like Redshift is architecturally different from a transactional database, not just 'a bigger database.'
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Key points
- •OLTP: many small fast transactions, low per-query latency matters, row-oriented storage (RDS/Aurora/DynamoDB)
- •OLAP: few large aggregate queries scanning huge row counts, columnar storage and parallel processing matter (Redshift)
- •Running OLAP queries against an OLTP database causes resource contention with live application traffic
- •Standard fix: a data pipeline extracting data into a purpose-built warehouse for analytical workloads