How to Choose Amazon Redshift Over MySQL

Why pick Amazon Redshift instead of MySQL?

Redshift’s columnar storage, MPP engine, and compression let analytic queries finish in seconds that take minutes or hours on row-based MySQL. Built-in spectrum access also queries S3 directly, avoiding ETL.

When does Redshift outperform MySQL?

Use Redshift when datasets exceed hundreds of GB, dashboards require sub-second refresh, or teams need concurrent scans over historical Orders and OrderItems.MySQL remains better for OLTP workloads with high per-row updates.

How does pricing differ?

Redshift charges by node-hour and data scanned; MySQL on RDS bills by instance size. For read-heavy analytics, Redshift’s compression (3–4×) and pause/resume cut costs.

What syntax changes should I expect?

Redshift follows PostgreSQL 8.0 but adds COPY, distkey, sortkey, and spectrum external tables.MySQL uses LOAD DATA INFILE and lacks columnar-storage options.

Example: Loading ecommerce data

In Redshift you issue a single COPY Orders FROM 's3://bucket/orders/' IAM_ROLE 'arn:...'; to parallel-ingest millions of rows, which beats MySQL’s row-by-row inserts.

Example: Aggregating lifetime value

Redshift leverages column pruning;
SELECT customer_id, SUM(total_amount) FROM Orders GROUP BY 1; scans only two compressed columns, whereas MySQL reads full rows.

Best practices for migration

1) Denormalize star schema; 2) choose distkey on large fact tables (e.g., customer_id); 3) apply sortkey on date columns like order_date; 4) batch loads via COPY.

Common pitfalls and fixes

Missing distribution keys: causes shuffling—assign a single high-cardinality column.
Too many small commits: group inserts in S3 files and use one COPY.

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