FREE Snowflake Virtual Dev Day '25

Skill up with AI and learn from visionaries Andrew Ng and Jared Kaplan on June 26.

Why Snowflake

Easy. Connected. Trusted.

Leading enterprises rely on the AI Data Cloud to power the end-to-end data lifecycle, from ingestion to sharing, so they can innovate faster and do more with their data. 

354%

Reported ROI by companies that use Snowflake for their data

754

The number of Forbes Global 2000 companies that use Snowflake1

Easily migrate to a modern platform

Whether moving from on-premises to the cloud or between clouds, Snowflake helps you have a seamless migration  journey — from any source.

Image of a snowflake bug surrounded by icons for migration platforms

Why Snowflake

Frequently Asked Questions

 

Snowflake is a cloud-agnostic platform and runs on the three major public cloud providers:

  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform (GCP)

This gives you the flexibility to choose the cloud provider that best suits your strategy.

 

Snowflake uses a flexible, consumption-based pricing model. Costs are based on two main components:
Compute: For compute resources, Snowflake employs a consumption-based model.
Storage: Storage costs are based on the amount of data (measured in terabytes per month) stored within Snowflake.
This model allows you to scale resources independently and optimize costs. Learn more about Snowflake pricing.

Yes, Snowflake offers a multi-cloud and cross-region experience. It runs on major cloud platforms (AWS, Azure and Google Cloud) across numerous global regions, providing flexibility, seamless data sharing and replication capabilities independent of the underlying cloud.

Snowflake has robust, enterprise-grade security and governance features built-in. This includes end-to-end encryption, granular role-based access control (RBAC), network policies, multi-factor authentication and comprehensive data governance capabilities (like data masking, tagging and access history) often managed through Snowflake Horizon Catalog.

Yes, Snowflake provides strong built-in support for AI and machine learning. Through Snowflake Cortex, you can access large language models (LLMs) and other AI-powered functions. Additionally, Snowpark ML allows users to build, train and deploy custom ML models using Python within Snowflake, keeping data secure and integrated.

You can visit our customer stories page or Inside the AI Data Cloud, the Snowflake blog, to read about customer success stories, case studies and use case examples.

Getting started with Snowflake is easy:

 

  1. Sign up for a free trial: Snowflake offers a 30-day free trial which includes free credits, allowing you to explore its features
  2. Explore quickstart guides: Snowflake provides hands-on tutorials that walk you through setting up your environment, loading data, performing various analytical tasks, from basic querying to more advanced analytics
  3. Join the community: Use Snowflake’s active community forums to learn best practices and get answers to your questions

Where Data Does More

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