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Amazon Redshift vs Snowflake
Redshift wins on AWS-native integration and cost if you are already deep in AWS; Snowflake wins on multi-cloud flexibility and cross-account data sharing.
Side by side
| Amazon Redshift | Snowflake | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Vendor | Amazon Web Services, Inc. | Snowflake Inc. | ||||||||||||||
| Pricing model | Usage-based | Usage-based | ||||||||||||||
| Free tier | Yes | No | ||||||||||||||
| Deployment | Cloud | Cloud | ||||||||||||||
| Open source | No | No | ||||||||||||||
| Best for | AWS-centric teams wanting a managed warehouse tightly integrated with the rest of the AWS data stack. | Teams wanting a fully managed, multi-cloud SQL warehouse with strong concurrency isolation and native data sharing. | ||||||||||||||
| Pricing | Provisioned clusters are billed hourly per node type; Redshift Serverless bills per RPU-hour with a per-second minimum; new Serverless users get trial credits and provisioned clusters offer a limited free-tier trial.
Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget. | Billed in per-second Snowflake credits whose price depends on edition (Standard, Enterprise, Business Critical, VPS), plus separate storage charges; a free trial is offered but there is no ongoing free tier.
Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget. | ||||||||||||||
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Verdict
Both are mature, widely deployed cloud data warehouses that separate storage from compute and bill on usage. The decision usually comes down to two things: how committed you already are to AWS, and how much you value querying data live across clouds and accounts without copying it.
Amazon Redshift runs only on AWS, which is a limitation if you are multi-cloud but an advantage if you are not — zero-ETL integrations pull data in directly from Aurora, RDS and DynamoDB, and Redshift Spectrum queries S3 data lake files without loading them first, all inside AWS's existing IAM and networking model. Snowflake runs on AWS, Azure or Google Cloud and is built around native cross-account and cross-cloud data sharing, letting customers exchange live data without copying it — a genuine advantage for organizations that share data with partners or across business units on different platforms.
Choose Amazon Redshift if
- Your data stack already lives on AWS and you want tight integration with Glue, S3, QuickSight and SageMaker.
- You want to query data lake files in S3 directly via Redshift Spectrum without a separate loading step.
- You are comfortable choosing between provisioned clusters and Redshift Serverless depending on workload shape.
Choose Snowflake if
- You are multi-cloud, or want the freedom to change cloud provider without re-platforming your warehouse.
- Sharing live data across accounts or organizations, without copying it, is a real requirement rather than a nice-to-have.
- You want a large ecosystem of connectors (Snowpark for Python/Java/Scala, most BI and ELT tools) built around one product.
What they share
Both isolate compute workloads from each other (Redshift via concurrency scaling and separate clusters, Snowflake via independently scalable virtual warehouses), both bill primarily on compute usage with storage priced separately, and both support semi-structured data alongside standard SQL. Neither has a self-hosted or on-premises option — both are managed-service-only.
Last reviewed September 22, 2026