Independent comparison for technology buyers. Updated May 2026.
Quick verdict: Choose Snowflake for multi-cloud portability, virtual warehouse isolation, and a mature data sharing marketplace. Choose Amazon Redshift when standardised on AWS, when tight integration with S3, Glue, and SageMaker is preferred, or when Redshift Serverless aligns with intermittent workloads. The differentiator is multi-cloud independent platform versus AWS-native warehouse with deep S3 lakehouse integration.
| Criteria | Snowflake | Amazon Redshift |
|---|---|---|
| Rating | 4.6 / 5.0 (3,800 reviews) | 4.2 / 5.0 (2,100 reviews) |
| Architecture | Multi-cluster shared data, virtual warehouses | RA3 nodes with managed storage, Redshift Serverless |
| Cloud Deployment | AWS, Azure, GCP (cross-cloud) | AWS only |
| Pricing Model | Per-second compute + storage credits | Node-hour or per-RPU serverless + storage |
| Compute Isolation | Per virtual warehouse, T-shirt sized | Per cluster or per workgroup (serverless) |
| Data Lake Integration | External tables, Iceberg tables | Spectrum on S3, Iceberg, Lake House |
| AI / ML | Cortex LLMs, Snowpark, ML functions | Redshift ML, SageMaker integration |
| Concurrency | Multi-cluster auto-scale | Concurrency scaling clusters |
| Best For | Multi-cloud, data sharing, mixed workloads | AWS-native, S3 lakehouse, SageMaker tie-ins |
Snowflake provides a cloud-agnostic data warehouse with strict separation of storage and compute. Workloads execute in virtual warehouses that can be sized, suspended, and scaled independently, isolating ETL from BI from data science. Snowflake also runs natively on AWS, Azure, and Google Cloud, with cross-cloud replication and Secure Data Sharing across organisations. Snowpark allows Python, Java, and Scala workloads to run inside the platform; Cortex exposes managed LLMs (Llama, Mistral, plus connectors) and ML functions accessible from SQL.
Amazon Redshift is AWS-native and tightly integrated with the wider AWS data stack. The RA3 architecture decouples storage (managed by Redshift Managed Storage on S3) from compute clusters. Redshift Serverless removes node management for spiky or intermittent workloads, billed in Redshift Processing Units. Redshift Spectrum queries data in S3 directly, and Redshift ML wraps SageMaker for in-database model training and inference. Federated queries reach into Aurora, RDS, and other AWS sources without ETL.
For multi-cloud or cross-organisation data sharing, Snowflake remains the natural fit. For AWS-centric estates where S3, Glue, Lake Formation, and SageMaker are already in place, Redshift typically delivers stronger integration economics. Compare further options in the data analytics category or evaluate against Snowflake vs Databricks and Snowflake vs BigQuery.
Snowflake pricing combines storage (around $23/TB/month compressed on AWS) with per-second compute on virtual warehouses (approximately $2-$4 per credit; credit burn scales with warehouse size). Enterprise annual spend typically lands between $300,000 and $10M, with cost discipline relying on auto-suspend, sizing, and workload isolation.
Amazon Redshift offers per-node provisioned pricing (RA3 dc2 from around $0.85/hour per node on demand, with reserved instance discounts) and Redshift Serverless from $0.36 per RPU-hour with an 8-RPU minimum. Storage on Redshift Managed Storage runs around $0.024/GB/month. Enterprise spend commonly lands between $200,000 and $8M ARR. Reserved capacity and pause-and-resume on serverless are the main optimisation levers.
Choose Snowflake when multi-cloud portability is a strategic requirement, when data sharing across business units or organisations is in scope, when virtual warehouse isolation across mixed workloads is needed, or when Snowpark and Cortex provide the development surface for data engineering and AI workloads.
Choose Amazon Redshift when the data estate is AWS-native, when tight integration with S3 (Spectrum, Iceberg), Glue, Lake Formation, and SageMaker matters, when Redshift Serverless aligns with intermittent workloads, or when AWS enterprise discount programs (EDP) make Redshift more economical at consolidated AWS scale.