Decision comparison
Snowflake vs Amazon Redshift
Choose Snowflake when cross-cloud operation, independent elastic compute, governed external sharing, and managed AI or pipeline capabilities are strategic requirements. Choose Amazon Redshift when analytics is centered on AWS, especially S3, Aurora/RDS, DynamoDB, SageMaker, and high-throughput MPP SQL workloads.
Direct comparison. These are reviewed substitutes bought for the same job, so the differences below are the ones that decide between them.
All 2 are cloud data warehouses.
Quick Comparison
| Decision factor | Snowflake | Amazon Redshift |
|---|---|---|
| Best For | Cross-cloud data platforms needing managed SQL analytics, governed sharing, continuous pipelines, and integrated ML or LLM deployment. | AWS-native analytics teams combining S3 data lakes, operational AWS databases, streaming sources, and high-performance SQL warehouse workloads. |
| Architecture | Fully managed cloud platform separating elastic compute from optimized compressed storage, with cross-cloud connectivity and Snowpark development support. | AWS-managed MPP warehouse using columnar storage, compression, zone maps, Redshift Serverless, and deep integrations with AWS services. |
| Pricing Model | Consumption-based pricing with no monthly or per-user price. Editions: Standard, Enterprise, Business Critical and Virtual Private Snowflake (VPS). The Service Consumption Table (effective October 2, 2026) lists on-demand prices per credit of $2.00 (Standard), $3.00 (Enterprise), $4.00 (Business Critical) and $6.00 (VPS) in AWS US East (Northern Virginia), and $2.60/$3.90/$5.20/$7.80 in AWS EU Dublin. On-demand storage is $23.00 per TB per month in AWS US East. Verified 2026-10-05 against https://www.snowflake.com/legal-files/CreditConsumptionTable.pdf. On-demand Platform Credit prices vary by cloud and region: Standard $2.00 to $3.25, Enterprise $3.00 to $4.90 and Business Critical $4.00 to $6.50 per credit. For example AWS AP Singapore lists $2.50 / $3.70 / $5.00, AWS Canada Central $2.25 / $3.50 / $4.50, and GCP Middle East Central 2 (Dammam) $3.25 / $4.90 / $6.50; on-demand storage in AWS AP Singapore is $25.00 per TB per month. Verified 2026-10-05 against https://www.snowflake.com/legal-files/CreditConsumptionTable.pdf. | Amazon Redshift bills by usage and publishes no monthly plan. Provisioned clusters start at $0.543 per node-hour; Serverless is billed per RPU-hour from $0.375 in US East (N. Virginia), charged per second. New Serverless accounts get a $300 credit expiring after 90 days -- a free trial, not a free tier. Verified 2026-09-16 against aws.amazon.com/redshift/pricing/. On-demand ra3.4xlarge nodes cost $3.26 per node-hour in US East (N. Virginia); AWS's own example prices four nodes for a 730-hour month at $9,519.20. Redshift Managed Storage is $0.024 per GB-month in the same region. Verified 2026-10-05 against https://aws.amazon.com/redshift/pricing/. |
| Ease of Use | Familiar ANSI SQL and fully managed infrastructure reduce operational work; users praise ease of use but mention importing and support friction. | SQL access and AWS integrations are strong for AWS teams; reviewers praise performance but report error-message, data-type, and stored-procedure issues. |
| Scalability | Elastic compute and Enterprise multi-cluster compute support concurrent workloads independently from storage, with Time Travel and disaster-recovery capabilities. | Concurrency Scaling handles high parallel demand; Serverless removes cluster management, while Multi-AZ and scalable multi-warehouse architectures support critical workloads. |
| Community/Support | User rating is 8.7/10 from 455 reviews; the Python connector repository has 726 stars and an Apache-2.0 license. | User rating is 8.9/10 from 218 reviews; the JDBC driver repository has 71 stars and a BSD-2-Clause license. |
Snowflake
- Best For:
- Cross-cloud data platforms needing managed SQL analytics, governed sharing, continuous pipelines, and integrated ML or LLM deployment.
- Architecture:
- Fully managed cloud platform separating elastic compute from optimized compressed storage, with cross-cloud connectivity and Snowpark development support.
- Pricing Model:
- Consumption-based pricing with no monthly or per-user price. Editions: Standard, Enterprise, Business Critical and Virtual Private Snowflake (VPS). The Service Consumption Table (effective October 2, 2026) lists on-demand prices per credit of $2.00 (Standard), $3.00 (Enterprise), $4.00 (Business Critical) and $6.00 (VPS) in AWS US East (Northern Virginia), and $2.60/$3.90/$5.20/$7.80 in AWS EU Dublin. On-demand storage is $23.00 per TB per month in AWS US East. Verified 2026-10-05 against https://www.snowflake.com/legal-files/CreditConsumptionTable.pdf. On-demand Platform Credit prices vary by cloud and region: Standard $2.00 to $3.25, Enterprise $3.00 to $4.90 and Business Critical $4.00 to $6.50 per credit. For example AWS AP Singapore lists $2.50 / $3.70 / $5.00, AWS Canada Central $2.25 / $3.50 / $4.50, and GCP Middle East Central 2 (Dammam) $3.25 / $4.90 / $6.50; on-demand storage in AWS AP Singapore is $25.00 per TB per month. Verified 2026-10-05 against https://www.snowflake.com/legal-files/CreditConsumptionTable.pdf.
- Ease of Use:
- Familiar ANSI SQL and fully managed infrastructure reduce operational work; users praise ease of use but mention importing and support friction.
- Scalability:
- Elastic compute and Enterprise multi-cluster compute support concurrent workloads independently from storage, with Time Travel and disaster-recovery capabilities.
- Community/Support:
- User rating is 8.7/10 from 455 reviews; the Python connector repository has 726 stars and an Apache-2.0 license.
Amazon Redshift
- Best For:
- AWS-native analytics teams combining S3 data lakes, operational AWS databases, streaming sources, and high-performance SQL warehouse workloads.
- Architecture:
- AWS-managed MPP warehouse using columnar storage, compression, zone maps, Redshift Serverless, and deep integrations with AWS services.
- Pricing Model:
- Amazon Redshift bills by usage and publishes no monthly plan. Provisioned clusters start at $0.543 per node-hour; Serverless is billed per RPU-hour from $0.375 in US East (N. Virginia), charged per second. New Serverless accounts get a $300 credit expiring after 90 days -- a free trial, not a free tier. Verified 2026-09-16 against aws.amazon.com/redshift/pricing/. On-demand ra3.4xlarge nodes cost $3.26 per node-hour in US East (N. Virginia); AWS's own example prices four nodes for a 730-hour month at $9,519.20. Redshift Managed Storage is $0.024 per GB-month in the same region. Verified 2026-10-05 against https://aws.amazon.com/redshift/pricing/.
- Ease of Use:
- SQL access and AWS integrations are strong for AWS teams; reviewers praise performance but report error-message, data-type, and stored-procedure issues.
- Scalability:
- Concurrency Scaling handles high parallel demand; Serverless removes cluster management, while Multi-AZ and scalable multi-warehouse architectures support critical workloads.
- Community/Support:
- User rating is 8.9/10 from 218 reviews; the JDBC driver repository has 71 stars and a BSD-2-Clause license.
Need the cost answer?
Compare Snowflake, BigQuery and Amazon Redshift Serverless using your workload.
Public signals
Verified factual signals only. Bars appear only for like-for-like metrics with five weekly assessments for every tool; missing evidence stays explicit. These signals do not establish enterprise adoption, product quality, or total cost.
| Metric | Snowflake | Amazon Redshift |
|---|---|---|
| GitHub commits, 90d(Developer adoption) | 68 | 12 |
| GitHub stars(Developer adoption) | 733 | 71 |
| Search interest(Market interest) | 1 | 1 |
| Hacker News mentions, 90d(Community interest) | 0 | 0 |
| npm weekly downloads(Developer adoption) | 3.7M | 451.2k |
| PyPI weekly downloads(Developer adoption) | 25.5M | 13.0M |
| Stack Overflow questions(Community interest) | 12.2k | 8.8k |
| Product Hunt comments(Community interest) | Not available | 1 |
| Product Hunt reviews(Community interest) | Not available | 0 |
| Product Hunt votes(Community interest) | Not available | 68 |
As of November 9, 2026 — updated weekly.
Health & risk evidence
Observed public-source checks for mapped package versions and repositories.
Snowflake
November 9, 2026Package vulnerabilities
PyPI · snowflake-connector-python@5.2.0 · npm · snowflake-sdk@3.4.1
0 vulnerabilities
across 2 packages
Repository security score
github.com/snowflakedb/snowflake-connector-python
4.3/10
Amazon Redshift
November 9, 2026Package vulnerabilities
npm · @aws-sdk/client-redshift@3.1164.0 · PyPI · redshift-connector@2.2.0
0 vulnerabilities
across 2 packages
Repository security score
github.com/aws/amazon-redshift-jdbc-driver
5.0/10
Interface Preview
Snowflake
Amazon Redshift
Feature Comparison
| Feature | Snowflake | Amazon Redshift |
|---|---|---|
| Compute and query architecture | ||
| Compute-storage design | Separates fully managed elastic compute from optimized compressed storage. | Uses MPP clusters with columnar storage and compression. |
| Concurrent query handling | Enterprise multi-cluster compute expands capacity for concurrent workloads. | Concurrency Scaling adds capacity for thousands of concurrent queries. |
| Query acceleration | Elastic warehouses scale compute without changing stored data. | Zone maps, compression, and MPP accelerate large-table scans. |
| Data lake and interoperability | ||
| Open table formats | Interoperates with open table formats across the platform. | Queries Apache Iceberg and Parquet data in data lakes. |
| Object storage analytics | Optimized platform storage supports governed analytical data workloads. | Spectrum runs SQL directly against Amazon S3 data lake files. |
| Operational data integration | Builds continuous pipelines in the language of choice. | Zero-ETL connects Aurora, RDS, and DynamoDB for near-real-time analytics. |
| Security and resilience | ||
| Encryption | Automatically encrypts all data in the Standard tier. | Encrypts traffic with TLS and data with AES-256. |
| Governance controls | Provides universal security, governance, observability, and Enterprise privacy controls. | Applies IAM Identity Center plus row-level and column-level permissions. |
| Availability and recovery | Business Critical provides failover, failback, and private connectivity. | Multi-AZ deployment targets a 99.99% SLA. |
| Analytics and development | ||
| SQL experience | Offers familiar ANSI SQL for managed analytical workloads. | Provides SQL analytics with Oracle SQL familiarity reported by users. |
| Machine learning and AI | Securely creates and deploys customized LLM and ML models. | Powers SQL analytics in the next generation of SageMaker. |
| Precomputed results | Time Travel retains historical data for recovery and analysis. | Materialized views support incremental refresh of query results. |
| Cloud ecosystem and sharing | ||
| Cloud deployment | Runs across major clouds through a cross-cloud ecosystem. | Integrates deeply with AWS analytics and operational services. |
| Live data collaboration | Shares live data securely across clouds and organizations. | Uses AWS-native integrations for connected analytics workflows. |
| Identity integration | Uses always-on unified platform security and governance. | Unifies identities through AWS IAM Identity Center. |
Compute and query architecture
Compute-storage design
Concurrent query handling
Query acceleration
Data lake and interoperability
Open table formats
Object storage analytics
Operational data integration
Security and resilience
Encryption
Governance controls
Availability and recovery
Analytics and development
SQL experience
Machine learning and AI
Precomputed results
Cloud ecosystem and sharing
Cloud deployment
Live data collaboration
Identity integration
Which to choose
Choose Snowflake when cross-cloud operation, independent elastic compute, governed external sharing, and managed AI or pipeline capabilities are strategic requirements. Choose Amazon Redshift when analytics is centered on AWS, especially S3, Aurora/RDS, DynamoDB, SageMaker, and high-throughput MPP SQL workloads.
Best-fit scenarios
Choose Snowflake if:
Choose Snowflake for multi-cloud organizations, teams that need secure live data sharing across organizations, or workloads benefiting from independent storage and elastic multi-cluster compute.
Choose Amazon Redshift if:
Choose Amazon Redshift for AWS-native teams needing S3 lake queries, Zero-ETL ingestion from AWS operational databases, Multi-AZ deployment, and Concurrency Scaling.
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
What is the main difference between Snowflake and Amazon Redshift?
Snowflake is a fully managed, cross-cloud data platform that separates elastic compute from storage and supports governed live data sharing across organizations. Amazon Redshift is an AWS-managed MPP warehouse built around columnar storage, compression, and zone maps. Redshift is particularly integrated with S3, Glue, SageMaker, QuickSight, Aurora/RDS, and DynamoDB; Snowflake emphasizes cross-cloud connectivity, open table formats, Snowpark, and its unified governance model.
Which is better for small teams?
For a small team already standardized on AWS, Amazon Redshift can be a practical fit because new Serverless accounts get a $300 credit for 90 days, and user feedback specifically identifies small teams as a strength. Snowflake may suit small teams that prioritize minimal infrastructure administration and familiar SQL: it publishes no monthly price and bills Standard on consumption at $2.00 per credit on-demand in AWS US East, including managed elastic compute, encryption, Snowpark, sharing, compression, and Time Travel. Evaluate expected usage because both have usage-based elements.
Can I migrate from Snowflake to Amazon Redshift?
Yes, but migration is an engineering project rather than a simple database switch. Both platforms support SQL analytics, so tables, transformations, and reporting queries can be assessed and ported, but Snowflake-specific features such as Snowpark, Time Travel, secure cross-cloud sharing, and multi-cluster warehouse behavior require redesign or replacement. In Redshift, teams should validate distribution and workload design, MPP query behavior, materialized-view refreshes, IAM-based permissions, S3/Spectrum access, and any AWS Zero-ETL integration requirements before cutover.
What are the pricing differences?
Snowflake’s published pricing includes a 30-day trial and no monthly price: credits are $2.00 (Standard), $3.00 (Enterprise) and $4.00 (Business Critical) on-demand in AWS US East, varying by region. Amazon Redshift’s published pricing includes a $300 credit for 90 days rather than a free tier, and usage-based rates from $0.543 per node-hour. Its official pricing also covers hourly on-demand nodes, Reserved Instances, bytes scanned by Spectrum, and per-second Concurrency Scaling beyond earned credits.