Analysts run complex SQL joins over terabytes of curated data several times a day, need sub-minute response, and concurrency for ~50 users. Which engine fits best?
A.Amazon Athena
Athena is serverless and great for occasional ad-hoc queries — but repeated heavy joins at 50-user concurrency favor provisioned MPP.
B.Amazon Redshift
Correct. Purpose-built warehouse for frequent complex SQL and concurrency.
C.Amazon EMR with Hive
EMR+Hive can run SQL but means managing clusters — overkill versus a warehouse.
D.AWS Glue interactive sessions
Glue interactive sessions are for developing ETL, not serving analyst dashboards.
Why this answer
Redshift is the data warehouse: MPP query engine, materialized views, concurrency scaling — built for repeated complex SQL at interactive speed with many concurrent users. Athena suits ad-hoc/sporadic queries; EMR suits big-data processing frameworks.
Correct answer: B · Last reviewed 2026-10-26
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