Choosing a cloud data warehouse is a multi-year commitment. Snowflake, BigQuery, and Redshift each have a distinct architecture, pricing model, and ecosystem. This comparison gives you the decision framework a real team would use in 2026.
Architecture
- Snowflake — virtual warehouses on shared storage + compute separation.
- BigQuery — serverless, separates compute from storage natively.
- Redshift — provisioned clusters (RA3 separates compute from managed storage).
Pricing model
- Snowflake — per-second compute + storage. Auto-suspend aggressively.
- BigQuery — pay per query (bytes scanned) or flat-rate slots.
- Redshift — node-based, RI discounts, Serverless option.
Performance
- Snowflake — multi-cluster warehouses for high concurrency.
- BigQuery — slots determine query throughput; BI Engine for low-latency.
- Redshift — sortkey + distkey tuning; concurrency scaling for spikes.
Which to pick
- Multi-cloud + shared storage — Snowflake.
- Google ecosystem, ML-heavy — BigQuery.
- AWS-only, deep Redshift Spectrum — Redshift.
Further reading
Authoritative sources
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