Salesforce Data Cloud vs Snowflake: The Basics

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There’s a fair bit of confusion about Salesforce Data Cloud and Snowflake Data Cloud. Given the name similarities, this isn’t surprising! However, when it comes to assessing Salesforce Data Cloud vs Snowflake, there actually shouldn’t be competition...


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Anton Minnion

3 mins


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Table of Contents
How are Data Cloud and Snowflake different?
The Salesforce to Snowflake integration
Use cases for Salesforce Data Cloud & Snowflake
Now, I’m not recommending you dash out and implement Snowflake just because you’re using Data Cloud, or vice versa - especially if your business is only just rolling out Salesforce Data Cloud!

What I am saying is: should it make sense for your business and your budgets allow for it, you can reap the benefits of both.

How are Data Cloud and Snowflake different?
To be clear, Salesforce does not own Snowflake. Rather Salesforce and Snowflake as separate companies have a partnership aimed at bringing together data storage and analytics insights for their customers.

There is a native integration between Data Cloud and Snowflake that country code nepal has been improved even further in 2023 with enhanced data sharing. But more on that later, let’s start with the basics…

Snowflake
Snowflake is a fully-fledged data warehouse, which means it’s designed entirely for secure, scalable data storage and enabling teams to work on standard datasets without limitations. It has incredibly advanced analytics and reporting potential, allowing for optimal performance regardless of the volume of data in the system or the complexity of data transformations.

Salesforce Data Cloud
Salesforce Data Cloud, on the other hand, is a customer data platform (CDP) that enables teams to see a unified profile of their customer and act on this instantly via marketing, advertising, service or sales activity.

The focus is on combining first-party data from multiple sources in order to execute more accurate and real-time communication. There are, however, limits around what data scientists and engineering teams can do with data transformation in Data Cloud, due to reporting limits and other factors.