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Salesforce Data Cloud vs Snowflake: The Basics

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...

Coloured background with text Salesforce Data Cloud vs 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 has been improved even further in 2023 with enhanced data sharing. But more on that later, let’s start with the basics…


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.

When using the cloud-based softwares together though, enterprise businesses have the complete infrastructure to store, manage, activate and report on data with ease.

The Salesforce to Snowflake integration

For years, a native database integration for Snowflake and Salesforce has made it possible for users to connect their platforms quickly and seamlessly.

In Salesforce, your Snowflake Connector options include:

  • Snowflake Connector - importing Snowflake data into CRM Analytics.

  • Snowflake Output Connector - pushing data into your Snowflake data warehouse.

  • Snowflake Direct Connector - live access to Snowflake data from Salesforce.

  • Third-Party Connectors to Snowflake - supports syncing and moving data between Salesforce, Snowflake and third-party cloud applications.

Historically, the data has been copied from Snowflake to Salesforce and vice versa, in scheduled batches.

As part of the Salesforce Winter ’24 release, Salesforce announced their new Data Share feature. Instead of copying the data, it is ‘shared’ between Snowflake and Salesforce Data Cloud with Zero ETL (Extract Transform Load). This eliminates drawbacks such as query time and delayed data syncing, and makes using and analysing the data instant.

In a nutshell, the integration allows users and AI features like Einstein, real-time access to data. Once the upcoming Bring-Your-Own-Lake (BYOL) Data Federation launches, this will be fully bi-directional. 

Use cases for Salesforce Data Cloud & Snowflake

Obviously with a breadth of data available to businesses of all industries, the use cases for combining Data Cloud and Snowflake are endless. A few of the most obvious are:

  • Using transactional customer data in Data Cloud alongside product data collected via POS or ecommerce platform and stored in Snowflake. Gaining insights about purchase behaviour and product categories to inform both reporting and machine-learning.

  • Analysing Sales Cloud data stored in Data Cloud with third-party data found in ‘The Snowflake Marketplace’; a resource for users containing live data sets from third-party providers. The combination of first and third party data can inform strategies, sales tactics, and ultimately deliver more sales and revenue.

  • Reviewing advanced website data in Snowflake with customer data points in Data Cloud to run informed, sophisticated and AI-driven segmentation and achieve better marketing conversion rates.

Hopefully, what this blog article has made clear is that it’s not ‘Salesforce Data Cloud vs Snowflake’ but ‘Salesforce Data Cloud and Snowflake’!

As complementary softwares that can really take data warehousing and activation to the next level, any ambitious business should be exploring their options for both. 

If you’d like to have a chat about Salesforce Data Cloud or how to integrate and use this with Snowflake, get in touch. We have data scientists and certified Salesforce developers available and ready to help!

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Anton Minnion

A data scientist and engineer, Anton has extensive experience in successfully delivering martech and salestech solutions for a variety of clients, both big and small, and across 25 countries. With a scary amount of knowledge in the development space, his focus at MarCloud is on innovating technical solutions for clients but also creating brand new apps and products for Salesforce platforms, to solve common business challenges.

Featured resource

Cover with text Salesforce Data Cloud 101

Salesforce Data Cloud 101

By the end of ‘Salesforce Data Cloud 101’ you’ll understand exactly what the software does and how it empowers business activities with real-time data about your customers. In 2023, Salesforce granted all Enterprise and Ultimate Sales Cloud users access to a free Data Cloud account. If your business is one of the lucky ones, the eBook will help you to feel more confident planning your implementation.

Download now

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