Basic Information
| Field | Details |
|---|---|
| English name | Amazon Redshift |
| Full name | Amazon Redshift |
| Chinese description | 云数据仓库 |
| Japanese description | クラウドデータウェアハウス |
| Exam frequency | ⭐⭐⭐⭐ |
| Often confused with | RDS / Athena |
In one sentence
AWS cloud data warehouse for long-running, frequent, and complex analytical SQL and BI workloads.
Key points
- It is optimized for analytical storage and execution over large historical datasets.
- It commonly works with an S3 data lake, Glue, Data Firehose, and QuickSight.
- Redshift is not an OLTP database and does not replace RDS or DynamoDB for transactions.
Exam focus
- Cloud data warehouse, complex BI, and frequent long-term analytics point to Redshift.
- Use Athena for ad hoc SQL directly over S3.
Common pitfalls
- Do not choose by product name alone; confirm data type, latency, control, operations, and cost constraints.
Remember
Redshift for sustained complex analytics; Athena for ad hoc S3 queries.