The startup’s main value proposition is that it makes it easier and cheaper for businesses to analyze data they’ve shelved away on the cloud—including the massive datasets needed to train machine learning algorithms. Because Snowflake structures its software differently, it can run resource-intensive AI programs more efficiently than its competitors, including juggernauts like Amazon’s AWS and Microsoft’s Azure.
Snowflake is only able to take on a dominant, entrenched competitor like AWS because it has come up with a better solution for one problem: allowing companies to cheaply expand their reliance on AI to help them with an ever-growing set of business decisions.
AI requires two key ingredients: huge troves of data and a lot of computing power. If you have both, you can monitor the performance of your business in granular detail (and in real time) to predict future conditions.
Snowflake differentiates itself from competitors like AWS through its software architecture. The company divides its massive pool of computing power into three groups: One is dedicated to storing data, another is just for analyzing that data, and the third is a brain that keeps the other two running. The system can dedicate more resources to storage or data analysis on the fly, depending on demand.
