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Amazon RedShift vs Snowflake
Amazon RedShift and Snowflake are both Data Storage & Warehousing tools. Here is how they compare on pricing, free plans, AI integrations and platforms, and when each is the better fit.
Side by side
| Feature | Amazon RedShift | Snowflake |
|---|---|---|
| Category | Data Storage & Warehousing | Data Storage & Warehousing |
| Pricing | Pay-as-you-go | Consumption-based |
| Free option | Yes | Not listed |
| AI integrations | MCP server, Claude, ChatGPT | MCP server, Claude, Microsoft Copilot |
| Links | Amazon RedShift listingVisit website (opens in a new tab) | Snowflake listingVisit website (opens in a new tab) |
Which to choose
Choose Amazon RedShift if
- already store your data in S3 data lakes and use the wider AWS ecosystem
- want a choice between manually configured clusters and serverless auto-scaling
- prefer to build and train machine learning models using standard SQL syntax
- want a two-month free trial tier for new accounts to test the platform
Choose Snowflake if
- need a multi-cloud architecture that runs across AWS, Microsoft Azure, and Google Cloud Platform
- work with unstructured media alongside structured and semi-structured datasets
- want to build data pipelines and machine learning workflows in Python, Java, or Scala as well as SQL
- prefer a fully managed platform that needs minimal infrastructure configuration
Verdict
Amazon Redshift suits organisations heavily invested in Amazon Web Services that want direct SQL querying across operational databases and S3 data lakes. It gives teams the choice between manually configured clusters for steady workloads and serverless scaling for variable demand. The trade-off is potential platform lock-in, egress charges when moving data outside AWS, and the need for specialist AWS knowledge to configure clusters and optimise queries.
Snowflake fits teams that operate across multiple cloud providers, including AWS, Azure, and Google Cloud Platform, or want minimal infrastructure management. It handles unstructured data alongside structured and semi-structured formats, and supports Python, Java, and Scala in addition to SQL. However, its credit-based consumption pricing can be hard to forecast, and advanced governance or disaster recovery features require higher pricing tiers.
FAQ
- How do Amazon Redshift and Snowflake structure their pricing?
Both platforms use usage-based pricing models. Amazon Redshift operates on a pay-as-you-go basis and includes a two-month free trial for new accounts. Snowflake uses consumption-based credit pricing where compute and storage expenses are billed separately, and a free option is not listed.
- Which clouds do Amazon Redshift and Snowflake run on?
Amazon Redshift is an Amazon Web Services product that integrates deeply with the AWS ecosystem. Snowflake features a multi-cloud architecture that deploys across Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
- What types of data and programming languages do they support?
Amazon Redshift runs SQL queries across structured and semi-structured data, and lets developers build machine learning models using SQL. Snowflake supports structured, semi-structured, and unstructured data, and allows development in Python, Java, Scala, and SQL through Snowpark.
- How do their AI integrations compare?
Amazon Redshift connects with Amazon Bedrock for generative AI and offers MCP servers for Claude Desktop alongside an AWS Data Analytics plugin for ChatGPT Work. Snowflake provides Cortex AI for running LLMs and conversational agents, plus a Snowflake-managed MCP server, Cortex Code in Claude Code, and Cortex Agents for Microsoft 365 Copilot.