How to Choose Amazon Redshift Over ClickHouse in PostgreSQL Workflows

Why prefer Redshift for fully managed analytics?

Redshift is a turnkey, AWS-managed MPP warehouse. Amazon automates scaling, patching, backups, and cross-AZ replication, removing ops burden. ClickHouse self-hosting demands cluster orchestration, upgrades, and monitoring—time-consuming for lean data teams.

How does Redshift simplify SQL development?

Redshift supports nearly full ANSI SQL 2011, window functions, common table expressions, and subqueries. ClickHouse’s SQL dialect is fast but omits standard JOIN types, MERGE, and correlated subqueries, forcing work-arounds.

When is Redshift’s concurrency scaling valuable?

BI dashboards send hundreds of short queries. Redshift’s Concurrency Scaling instantly adds on-demand clusters, preserving SLA without manual sharding. ClickHouse saturates CPU under bursty loads unless over-provisioned.

What ecosystem advantages does Redshift offer?

Redshift Spectrum queries S3, federated queries reach RDS/PostgreSQL, and AWS Glue catalogs tables. These native integrations streamline ELT. ClickHouse requires third-party connectors or custom Spark jobs.

How does Redshift handle semi-structured data?

SUPER data type plus PartiQL lets you store and query JSON with relational SQL. ClickHouse’s JSON functions exist but lack a dedicated dynamic type and require more transforms.

Best practice: define DISTKEY and SORTKEY

Choose a high-cardinality column (e.g., orders.id) as DISTKEY to co-locate joins, and a frequently filtered column (order_date) as SORTKEY to prune blocks. This boosts join speed and reduces I/O.

Example: daily revenue per product

Query illustrates Redshift syntax and performance tips.

WITH daily_sales AS (
SELECT oi.product_id,
o.order_date::date AS sales_day,
SUM(oi.quantity * p.price) AS revenue
FROM orders o
JOIN orderitems oi USING (order_id)
JOIN products p ON p.id = oi.product_id
WHERE o.order_date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY oi.product_id, sales_day
)
SELECT *
FROM daily_sales
ORDER BY revenue DESC;


Common mistake: ignoring WLM queues

Running all jobs in the default queue leads to lock contention. Create separate WLM queues for ETL and BI, assign query groups, and enable Short Query Acceleration for snappy dashboards.

Common mistake: treating Redshift like OLTP

Row-by-row INSERTs cause commit bloat. Batch load via COPY from S3 or staged temp tables in 10,000+ row chunks.

Redshift vs ClickHouse cost considerations?

RA3 nodes separate compute and storage, letting you pause or downscale dev clusters. ClickHouse Cloud now offers similar elasticity, but enterprise support pricing may offset savings.

Takeaway

Choose Redshift when you need a managed, ANSI-compliant warehouse that scales concurrency, integrates with AWS, and minimizes dev-ops. Opt for ClickHouse when sub-second latency on append-only event data is your top priority.